The recursive-least-squares (RLS) algorithm was introduced as an alternative to LMS algorithm with enhanced performance. Computational complexity and instability in updating the autocolleltion matrix are some of the drawbacks of the RLS algorithm that were among the reasons for the intrduction of the second-order recursive inverse (RI) adaptive algorithm. The 2nd order RI adaptive algorithm suffered from low convergence rate in certain scenarios that required a relatively small initial step-size. In this paper, we propose a newsecond-order RI algorithm that projects the input signal to a new domain namely discrete-wavelet-transform (DWT) as pre step before performing the algorithm. This transformation overcomes the low convergence rate of the second-order RI algorithm by reducing the self-correlation of the input signal in the mentioned scenatios. Expeirments are conducted using the noise cancellation setting. The performance of the proposed algorithm is compared to those of the RI, original second-order RI and RLS algorithms in different Gaussian and impulsive noise environments. Simulations demonstrate the superiority of the proposed algorithm in terms of convergence rate comparedto those algorithms.
Discrete wavelet transform-based RI adaptive algorithm for system identificationIJECEIAES
In this paper, we propose a new adaptive filtering algorithm for system identifica- tion. The algorithm is based on the recursive inverse (RI) adaptive algorithm which suffers from low convergence rates in some applications; i.e., the eigenvalue spread of the autocorrelation matrix is relatively high. The proposed algorithm applies discrete-wavelet transform (DWT) to the input signal which, in turn, helps to overcome the low convergence rate of the RI algorithm with relatively small step-size(s). Different scenarios has been investigated in different noise environments in system identification setting. Experiments demonstrate the advantages of the proposed DWT recursive inverse (DWT-RI) filter in terms of convergence rate and mean-square-error (MSE) compared to the RI, discrete cosine transform LMS (DCT-LMS), discretewavelet transform LMS (DWT-LMS) and recursive-least-squares (RLS) algorithms under same conditions.
A Review: Compensation of Mismatches in Time Interleaved Analog to Digital Co...IJERA Editor
The execution of today's correspondence frameworks is exceedingly subject to the utilized Analog-to-Digital converters (ADCs), and with a specific end goal to give more flexibility and exactness to the developing correspondence innovations, superior-ADCs are needed. In this respect, the time-interleaved operation of an exhibit of ADCs (TI-ADC) might be a sensible result. A TI-ADC can build its throughput by utilizing M channel ADCs or sub converters in parallel and examining the data motion in a period-interleaved way. In any case, the execution of a TI-ADC gravely suffers from the bungles around the channel ADCs. In this paper we survey the advancement in the configuration of low-intricacy advanced remedy structures and calculations for time-interleaved ADCs in the course of the most recent five years. We devise a discrete-time model, state the outline issue, and finally infer the calculations and structures. Specifically, we examine proficient calculations to outline time-differing remedy filters and additionally iterative structures using polynomial based filters. Thusly, the remuneration structure may be utilized to repay time-differing recurrence reaction befuddles in time-interleaved ADCs, and in addition to remake uniform examples from nonuniformly tested indicators. We examine the recompense structure, research its execution, and exhibit requisition zones of the structure through various illustrations. At long last, we give a standpoint to future examination questions.
Singular Value Decomposition: Principles and Applications in Multiple Input M...IJCNCJournal
The authors discuss the importance of using the singular value decomposition (SVD) in computing the capacity of multiple input multiple output (MIMO) and in estimation the channel gain from the transmitter to the receiver. Examples that show how the SVD simplifies computing the MIMO channel capacity are discussed. Numerical results that show what factors determine the performance of using SVD in channel
estimation are also discussed.
Mitigating Interference to GPS Operation Using Variable Forgetting Factor Bas...IJCNCJournal
In this paper, an interference method based on signal processing is proposed. The approach is based on
utilizing the maximum likelihood properties of the received signal. The approach is built on maximizing the
probability of the desired data. The GPS data, which is constructed using Binary Phase Shift Keying
(BPSK) modulation, is transmitted as “1’s” and as “0’s.” carried on 1575.42MHz carrier called the L1
frequency. The statistics of the GPS data and interference are utilized in terms of their distribution and
variance. The statistics are used to update (adaptively) the forgetting factor (Lambda) of the Recursive
Least Squares (RLS) filter. The proposed method is called Maximum Likelihood Variable Forgetting Factor
(ML VFF). The adaptive update takes on assigning lambda to the maximum of the probabilities of the
symbols based on the statistics mentioned.
DESIGN OF DELAY COMPUTATION METHOD FOR CYCLOTOMIC FAST FOURIER TRANSFORMsipij
In this paper the Delay Computation method for Common Sub expression Elimination algorithm is being implemented on Cyclotomic Fast Fourier Transform. The Common Sub Expression Elimination algorithm is combined with the delay computing method and is known as Gate Level Delay Computation with Common Sub expression Elimination Algorithm. Common sub expression elimination is effective
optimization method used to reduce adders in cyclotomic Fourier transform. The delay computing method is based on delay matrix and suitable for implementation with computers. The Gate level delay computation method is used to find critical path delay and it is analyzed on various finite field elements. The presented algorithm is established through a case study in Cyclotomic Fast Fourier Transform over finite field. If Cyclotomic Fast Fourier Transform is implemented directly then the system will have high additive complexities. So by using GLDC-CSE algorithm on cyclotomic fast Fourier transform, the additive
complexities will be reduced and also the area and area delay product will be reduced.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Discrete wavelet transform-based RI adaptive algorithm for system identificationIJECEIAES
In this paper, we propose a new adaptive filtering algorithm for system identifica- tion. The algorithm is based on the recursive inverse (RI) adaptive algorithm which suffers from low convergence rates in some applications; i.e., the eigenvalue spread of the autocorrelation matrix is relatively high. The proposed algorithm applies discrete-wavelet transform (DWT) to the input signal which, in turn, helps to overcome the low convergence rate of the RI algorithm with relatively small step-size(s). Different scenarios has been investigated in different noise environments in system identification setting. Experiments demonstrate the advantages of the proposed DWT recursive inverse (DWT-RI) filter in terms of convergence rate and mean-square-error (MSE) compared to the RI, discrete cosine transform LMS (DCT-LMS), discretewavelet transform LMS (DWT-LMS) and recursive-least-squares (RLS) algorithms under same conditions.
A Review: Compensation of Mismatches in Time Interleaved Analog to Digital Co...IJERA Editor
The execution of today's correspondence frameworks is exceedingly subject to the utilized Analog-to-Digital converters (ADCs), and with a specific end goal to give more flexibility and exactness to the developing correspondence innovations, superior-ADCs are needed. In this respect, the time-interleaved operation of an exhibit of ADCs (TI-ADC) might be a sensible result. A TI-ADC can build its throughput by utilizing M channel ADCs or sub converters in parallel and examining the data motion in a period-interleaved way. In any case, the execution of a TI-ADC gravely suffers from the bungles around the channel ADCs. In this paper we survey the advancement in the configuration of low-intricacy advanced remedy structures and calculations for time-interleaved ADCs in the course of the most recent five years. We devise a discrete-time model, state the outline issue, and finally infer the calculations and structures. Specifically, we examine proficient calculations to outline time-differing remedy filters and additionally iterative structures using polynomial based filters. Thusly, the remuneration structure may be utilized to repay time-differing recurrence reaction befuddles in time-interleaved ADCs, and in addition to remake uniform examples from nonuniformly tested indicators. We examine the recompense structure, research its execution, and exhibit requisition zones of the structure through various illustrations. At long last, we give a standpoint to future examination questions.
Singular Value Decomposition: Principles and Applications in Multiple Input M...IJCNCJournal
The authors discuss the importance of using the singular value decomposition (SVD) in computing the capacity of multiple input multiple output (MIMO) and in estimation the channel gain from the transmitter to the receiver. Examples that show how the SVD simplifies computing the MIMO channel capacity are discussed. Numerical results that show what factors determine the performance of using SVD in channel
estimation are also discussed.
Mitigating Interference to GPS Operation Using Variable Forgetting Factor Bas...IJCNCJournal
In this paper, an interference method based on signal processing is proposed. The approach is based on
utilizing the maximum likelihood properties of the received signal. The approach is built on maximizing the
probability of the desired data. The GPS data, which is constructed using Binary Phase Shift Keying
(BPSK) modulation, is transmitted as “1’s” and as “0’s.” carried on 1575.42MHz carrier called the L1
frequency. The statistics of the GPS data and interference are utilized in terms of their distribution and
variance. The statistics are used to update (adaptively) the forgetting factor (Lambda) of the Recursive
Least Squares (RLS) filter. The proposed method is called Maximum Likelihood Variable Forgetting Factor
(ML VFF). The adaptive update takes on assigning lambda to the maximum of the probabilities of the
symbols based on the statistics mentioned.
DESIGN OF DELAY COMPUTATION METHOD FOR CYCLOTOMIC FAST FOURIER TRANSFORMsipij
In this paper the Delay Computation method for Common Sub expression Elimination algorithm is being implemented on Cyclotomic Fast Fourier Transform. The Common Sub Expression Elimination algorithm is combined with the delay computing method and is known as Gate Level Delay Computation with Common Sub expression Elimination Algorithm. Common sub expression elimination is effective
optimization method used to reduce adders in cyclotomic Fourier transform. The delay computing method is based on delay matrix and suitable for implementation with computers. The Gate level delay computation method is used to find critical path delay and it is analyzed on various finite field elements. The presented algorithm is established through a case study in Cyclotomic Fast Fourier Transform over finite field. If Cyclotomic Fast Fourier Transform is implemented directly then the system will have high additive complexities. So by using GLDC-CSE algorithm on cyclotomic fast Fourier transform, the additive
complexities will be reduced and also the area and area delay product will be reduced.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Design Of Area Delay Efficient Fixed-Point Lms Adaptive Filter For EEG Applic...IJTET Journal
An efficient architecture for the implementation of a delayed least mean square adaptive filter. A Novel
partial product Generator is achieving lower adaptation-delay and Area delay consumption and propose a strategy
for optimized balanced pipelining across the time-consuming combinational blocks of the structure. From synthesis
results, the proposed design will offers less area-delay product (ADP) the best of the existing systolic structures, on
average, for filter lengths N =8, 16, and 32. An efficient fixed-point implementation scheme of the proposed
architecture, The EEG(electroencephalogram) is used for recording of electrical activity of the brain .During
recording the EEG is contaminated by various artifacts as PLI(Power line interference), MA(Muscle artifact),
EBA(Eye blink artifact). This paper gives Detail of various artifacts which occur in EEG signal. In this we study
adaptive filter for reducing the EBA (eye blink artifact) noise from the EEG signal and to increase SNR (Signal to
noise ratio).the analytical result matches with the simulation result is showed.
Area, Delay and Power Comparison of Adder TopologiesVLSICS Design
Adders form an almost obligatory component of every contemporary integrated circuit. The prerequisite of the adder is that it is primarily fast and secondarily efficient in terms of power consumption and chip area. This paper presents the pertinent choice for selecting the adder topology with the tradeoff between delay, power consumption and area. The adder topology used in this work are ripple carry adder, carry lookahead adder, carry skip adder, carry select adder, carry increment adder, carry save adder and carry bypass adder. The module functionality and performance issues like area, power dissipation and propagation delay are analyzed at 0.12µm 6metal layer CMOS technology using microwind tool.
Improved Timing Estimation Using Iterative Normalization Technique for OFDM S...IJECEIAES
Conventional timing estimation schemes based on autocorrelation experience perfor- mance degradation in the multipath channel environment with high delay spread. To overcome this problem, we proposed an improvement of the timing estimation for the OFDM system based on statistical change of symmetrical correlator. The new method uses iterative normalization technique to the correlator output before the detection based on statistical change of symmetric correlator is applied. Thus, it increases the detection probability and achieves better performance than previously published methods in the multipath environment. Computer simulation shows that our method is very robust in the fading multipath channel.
Adaptive Channel Equalization for Nonlinear Channels using Signed Regressor F...IDES Editor
Wireless communication systems are affected by
inter-symbol interference (ISI), co-channel interference in
the presence of additive white Gaussian noise. ISI is primarily
due to the distortion caused by frequency and time selectivity
of the fading channel and it causes performance degradation.
Equalization techniques are used to mitigate the effect of ISI
and noise for better demodulation. This paper presents a novel
technique for channel equalization. Here a Signed Regressor
adaptive algorithm based on FLANN (Functional Link Artificial
Neural Network) has been developed for nonlinear channel
equalization along with the analysis of MSE and BER. The
results are compared with the conventional adaptive LMS
algorithm based FLANN model. The Signed Regressor FLANN
shows better performance as compared to LMS based FLANN.
The equalizer presented shows considerable performance
compared to the other adaptive structure for both the linear
and non-linear models in terms of convergence rate, MSE
and BER over a wide range.
GRAPH MATCHING ALGORITHM FOR TASK ASSIGNMENT PROBLEMIJCSEA Journal
Task assignment is one of the most challenging problems in distributed computing environment. An optimal task assignment guarantees minimum turnaround time for a given architecture. Several approaches of optimal task assignment have been proposed by various researchers ranging from graph partitioning based tools to heuristic graph matching. Using heuristic graph matching, it is often impossible to get optimal task assignment for practical test cases within an acceptable time limit. In this paper, we have parallelized the basic heuristic graph-matching algorithm of task assignment which is suitable only for cases where processors and inter processor links are homogeneous. This proposal is a derivative of the basic task assignment methodology using heuristic graph matching. The results show that near optimal assignments are obtained much faster than the sequential program in all the cases with reasonable speed-up.
BER Analysis ofImpulse Noise inOFDM System Using LMS,NLMS&RLSiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Performance Analysis of Ultra Wideband Receivers for High Data Rate Wireless ...graphhoc
For high data rate ultra wideband communication system, performance comparison of Rake, MMSE and Rake-MMSE receivers is attempted in this paper. Further a detail study on Rake-MMSE time domain equalizers is carried out taking into account all the important parameters such as the effect of the number of Rake fingers and equalizer taps on the error rate performance. This receiver combats inter-symbol interference by taking advantages of both the Rake and equalizer structure. The bit error rate performances are investigated using MATLAB simulation on IEEE 802.15.3a defined UWB channel models. Simulation results show that the bit error rate probability of Rake-MMSE receiver is much better than Rake receiver and MMSE equalizer. Study on non-line of sight indoor channel models illustrates that bit error rate performance of Rake-MMSE (both LE and DFE) improves for CM3 model with smaller spread compared to CM4 channel model. It is indicated that for a MMSE equalizer operating at low to medium SNR values, the number of Rake fingers is the dominant factor to improve system performance, while at high SNR values the number of equalizer taps plays a more significant role in reducing the error rate.
Analysis Predicted Location of Harmonic Distortion in RF Upconverter StructureTELKOMNIKA JOURNAL
A new mathematical analysis to predict the magnitude size of the distortion products from the
signal up-conversion process output is presented. The signal up-conversion process converts the digital
baseband from the analog baseband into a radio frequency signal. When the signal baseband involves
frequency offsetting then occurring a number of distortion products which can reduce the dynamic range
so it is difficult to meet the spectrum mask requirements within the operating band. This paper will focus on
methods of new mathematical analysis using a continuous frequency range and only applies to a single
side band tone, with constant amplitude into any value of frequency offsets. The novel contribution to the
analysis starts at generating the gate signal and convolution of the gate signal into the reference carrier
signal. The results show very close between the simulation results and the calculation of the predicted
location of the distortions.
Comparitive analysis of doa and beamforming algorithms for smart antenna systemseSAT Journals
Abstract This paper revolves around the implementation of Direction of arrival and Adaptive beam-forming algorithms for Smart Antenna Systems. This paper also investigates the implementation of algorithms on various planner array geometries viz. circular and rectangular. Music algorithm is primarily finds the possible location of desired user and adaptive beam-forming algorithms such as LMS, RLS and CMA algorithms adapts the weights of the array. DOA estimation gives the maximum peak of spectrum with respect to angle of arrival where the desired user is supposed to exist. After DOA estimation weights of array antenna are changed with the changing received signal. This methodology is called as Spectral estimation, which allows the antenna pattern to steer in desired direction estimated by DOA and simultaneously null out the interfering signals. Rate of convergence is the major criterion for comparison for adaptive beam-forming algorithms. Keywords: DOA, MUSIC, LMS, RLS, CMA, SAS.
A digital calibration algorithm with variable amplitude dithering for domain-...VLSICS Design
The pseudorandom noise dither (PN dither) technique is used to measure domain-extended pipeline
analog-to-digital converter (ADC) gain errors and to calibrate them digitally, while the digital error
correction technique is used to correct the comparator offsets through the use of redundancy bits. However,
both these techniques suffer from three disadvantages: slow convergence speed, deduction of the amplitude
of the transmitting signal, and deduction of the redundancy space. A digital calibration algorithm with
variable-amplitude dithering for domain-extended pipeline ADCs is used in this research to overcome these
disadvantages. The proposed algorithm is implemented in a 12-bit, 100 MS/s sample-rate pipeline ADC.
The simulation results illustrate both static and dynamic performance improvement after calibration.
Moreover, the convergence speed is much faster.
Channel Equalization of WCDMA Downlink System Using Finite Length MMSE-DFEIOSR Journals
Abstract: The performance of WCDMA system deteriorates in the presence of multipath fading environment. Fading destroys the orthogonality and is responsible for multiple access interference (MAI). Though conventional rake receiver provides reasonable performance in the WCDMA downlink system due to path diversity, but it does not restores the orthogonality. Linear equalizer restores orthogonality and suppresses MAI, but it is not efficient, since its performance depends on the spectral characteristics of the channel. To overcome this, Minimum Mean Square Error- Decision Feedback Equalizer (MMSE-DFE) with a linear, anticausal feedforward filter, causal feedback filter and simple detector is proposed in this paper. The filter taps of finite length DFE is derived using the cholesky factorization theory, capable of suppressing noise, Intersymbol Interference (ISI) and MAI. This paper describes the WCDMA downlink system using finite length MMSE-DFE and takes into consideration the effects of interference which includes additive white gaussian noise, multipath fading, ISI and MAI. Furthermore, the performance is compared with conventional rake receiver and MMSE and the simulation results are shown. Keywords – MMSE, MMSE-DFE, rake receiver, WCDMA
Channel Equalization of WCDMA Downlink System Using Finite Length MMSE-DFEIOSR Journals
The performance of WCDMA system deteriorates in the presence of multipath fading environment.
Fading destroys the orthogonality and is responsible for multiple access interference (MAI). Though
conventional rake receiver provides reasonable performance in the WCDMA downlink system due to path
diversity, but it does not restores the orthogonality. Linear equalizer restores orthogonality and suppresses
MAI, but it is not efficient, since its performance depends on the spectral characteristics of the channel. To
overcome this, Minimum Mean Square Error- Decision Feedback Equalizer (MMSE-DFE) with a linear,
anticausal feedforward filter, causal feedback filter and simple detector is proposed in this paper. The filter taps
of finite length DFE is derived using the cholesky factorization theory, capable of suppressing noise,
Intersymbol Interference (ISI) and MAI. This paper describes the WCDMA downlink system using finite length
MMSE-DFE and takes into consideration the effects of interference which includes additive white gaussian
noise, multipath fading, ISI and MAI. Furthermore, the performance is compared with conventional rake
receiver and MMSE and the simulation results are shown.
Design Of Area Delay Efficient Fixed-Point Lms Adaptive Filter For EEG Applic...IJTET Journal
An efficient architecture for the implementation of a delayed least mean square adaptive filter. A Novel
partial product Generator is achieving lower adaptation-delay and Area delay consumption and propose a strategy
for optimized balanced pipelining across the time-consuming combinational blocks of the structure. From synthesis
results, the proposed design will offers less area-delay product (ADP) the best of the existing systolic structures, on
average, for filter lengths N =8, 16, and 32. An efficient fixed-point implementation scheme of the proposed
architecture, The EEG(electroencephalogram) is used for recording of electrical activity of the brain .During
recording the EEG is contaminated by various artifacts as PLI(Power line interference), MA(Muscle artifact),
EBA(Eye blink artifact). This paper gives Detail of various artifacts which occur in EEG signal. In this we study
adaptive filter for reducing the EBA (eye blink artifact) noise from the EEG signal and to increase SNR (Signal to
noise ratio).the analytical result matches with the simulation result is showed.
Area, Delay and Power Comparison of Adder TopologiesVLSICS Design
Adders form an almost obligatory component of every contemporary integrated circuit. The prerequisite of the adder is that it is primarily fast and secondarily efficient in terms of power consumption and chip area. This paper presents the pertinent choice for selecting the adder topology with the tradeoff between delay, power consumption and area. The adder topology used in this work are ripple carry adder, carry lookahead adder, carry skip adder, carry select adder, carry increment adder, carry save adder and carry bypass adder. The module functionality and performance issues like area, power dissipation and propagation delay are analyzed at 0.12µm 6metal layer CMOS technology using microwind tool.
Improved Timing Estimation Using Iterative Normalization Technique for OFDM S...IJECEIAES
Conventional timing estimation schemes based on autocorrelation experience perfor- mance degradation in the multipath channel environment with high delay spread. To overcome this problem, we proposed an improvement of the timing estimation for the OFDM system based on statistical change of symmetrical correlator. The new method uses iterative normalization technique to the correlator output before the detection based on statistical change of symmetric correlator is applied. Thus, it increases the detection probability and achieves better performance than previously published methods in the multipath environment. Computer simulation shows that our method is very robust in the fading multipath channel.
Adaptive Channel Equalization for Nonlinear Channels using Signed Regressor F...IDES Editor
Wireless communication systems are affected by
inter-symbol interference (ISI), co-channel interference in
the presence of additive white Gaussian noise. ISI is primarily
due to the distortion caused by frequency and time selectivity
of the fading channel and it causes performance degradation.
Equalization techniques are used to mitigate the effect of ISI
and noise for better demodulation. This paper presents a novel
technique for channel equalization. Here a Signed Regressor
adaptive algorithm based on FLANN (Functional Link Artificial
Neural Network) has been developed for nonlinear channel
equalization along with the analysis of MSE and BER. The
results are compared with the conventional adaptive LMS
algorithm based FLANN model. The Signed Regressor FLANN
shows better performance as compared to LMS based FLANN.
The equalizer presented shows considerable performance
compared to the other adaptive structure for both the linear
and non-linear models in terms of convergence rate, MSE
and BER over a wide range.
GRAPH MATCHING ALGORITHM FOR TASK ASSIGNMENT PROBLEMIJCSEA Journal
Task assignment is one of the most challenging problems in distributed computing environment. An optimal task assignment guarantees minimum turnaround time for a given architecture. Several approaches of optimal task assignment have been proposed by various researchers ranging from graph partitioning based tools to heuristic graph matching. Using heuristic graph matching, it is often impossible to get optimal task assignment for practical test cases within an acceptable time limit. In this paper, we have parallelized the basic heuristic graph-matching algorithm of task assignment which is suitable only for cases where processors and inter processor links are homogeneous. This proposal is a derivative of the basic task assignment methodology using heuristic graph matching. The results show that near optimal assignments are obtained much faster than the sequential program in all the cases with reasonable speed-up.
BER Analysis ofImpulse Noise inOFDM System Using LMS,NLMS&RLSiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Performance Analysis of Ultra Wideband Receivers for High Data Rate Wireless ...graphhoc
For high data rate ultra wideband communication system, performance comparison of Rake, MMSE and Rake-MMSE receivers is attempted in this paper. Further a detail study on Rake-MMSE time domain equalizers is carried out taking into account all the important parameters such as the effect of the number of Rake fingers and equalizer taps on the error rate performance. This receiver combats inter-symbol interference by taking advantages of both the Rake and equalizer structure. The bit error rate performances are investigated using MATLAB simulation on IEEE 802.15.3a defined UWB channel models. Simulation results show that the bit error rate probability of Rake-MMSE receiver is much better than Rake receiver and MMSE equalizer. Study on non-line of sight indoor channel models illustrates that bit error rate performance of Rake-MMSE (both LE and DFE) improves for CM3 model with smaller spread compared to CM4 channel model. It is indicated that for a MMSE equalizer operating at low to medium SNR values, the number of Rake fingers is the dominant factor to improve system performance, while at high SNR values the number of equalizer taps plays a more significant role in reducing the error rate.
Analysis Predicted Location of Harmonic Distortion in RF Upconverter StructureTELKOMNIKA JOURNAL
A new mathematical analysis to predict the magnitude size of the distortion products from the
signal up-conversion process output is presented. The signal up-conversion process converts the digital
baseband from the analog baseband into a radio frequency signal. When the signal baseband involves
frequency offsetting then occurring a number of distortion products which can reduce the dynamic range
so it is difficult to meet the spectrum mask requirements within the operating band. This paper will focus on
methods of new mathematical analysis using a continuous frequency range and only applies to a single
side band tone, with constant amplitude into any value of frequency offsets. The novel contribution to the
analysis starts at generating the gate signal and convolution of the gate signal into the reference carrier
signal. The results show very close between the simulation results and the calculation of the predicted
location of the distortions.
Comparitive analysis of doa and beamforming algorithms for smart antenna systemseSAT Journals
Abstract This paper revolves around the implementation of Direction of arrival and Adaptive beam-forming algorithms for Smart Antenna Systems. This paper also investigates the implementation of algorithms on various planner array geometries viz. circular and rectangular. Music algorithm is primarily finds the possible location of desired user and adaptive beam-forming algorithms such as LMS, RLS and CMA algorithms adapts the weights of the array. DOA estimation gives the maximum peak of spectrum with respect to angle of arrival where the desired user is supposed to exist. After DOA estimation weights of array antenna are changed with the changing received signal. This methodology is called as Spectral estimation, which allows the antenna pattern to steer in desired direction estimated by DOA and simultaneously null out the interfering signals. Rate of convergence is the major criterion for comparison for adaptive beam-forming algorithms. Keywords: DOA, MUSIC, LMS, RLS, CMA, SAS.
A digital calibration algorithm with variable amplitude dithering for domain-...VLSICS Design
The pseudorandom noise dither (PN dither) technique is used to measure domain-extended pipeline
analog-to-digital converter (ADC) gain errors and to calibrate them digitally, while the digital error
correction technique is used to correct the comparator offsets through the use of redundancy bits. However,
both these techniques suffer from three disadvantages: slow convergence speed, deduction of the amplitude
of the transmitting signal, and deduction of the redundancy space. A digital calibration algorithm with
variable-amplitude dithering for domain-extended pipeline ADCs is used in this research to overcome these
disadvantages. The proposed algorithm is implemented in a 12-bit, 100 MS/s sample-rate pipeline ADC.
The simulation results illustrate both static and dynamic performance improvement after calibration.
Moreover, the convergence speed is much faster.
Channel Equalization of WCDMA Downlink System Using Finite Length MMSE-DFEIOSR Journals
Abstract: The performance of WCDMA system deteriorates in the presence of multipath fading environment. Fading destroys the orthogonality and is responsible for multiple access interference (MAI). Though conventional rake receiver provides reasonable performance in the WCDMA downlink system due to path diversity, but it does not restores the orthogonality. Linear equalizer restores orthogonality and suppresses MAI, but it is not efficient, since its performance depends on the spectral characteristics of the channel. To overcome this, Minimum Mean Square Error- Decision Feedback Equalizer (MMSE-DFE) with a linear, anticausal feedforward filter, causal feedback filter and simple detector is proposed in this paper. The filter taps of finite length DFE is derived using the cholesky factorization theory, capable of suppressing noise, Intersymbol Interference (ISI) and MAI. This paper describes the WCDMA downlink system using finite length MMSE-DFE and takes into consideration the effects of interference which includes additive white gaussian noise, multipath fading, ISI and MAI. Furthermore, the performance is compared with conventional rake receiver and MMSE and the simulation results are shown. Keywords – MMSE, MMSE-DFE, rake receiver, WCDMA
Channel Equalization of WCDMA Downlink System Using Finite Length MMSE-DFEIOSR Journals
The performance of WCDMA system deteriorates in the presence of multipath fading environment.
Fading destroys the orthogonality and is responsible for multiple access interference (MAI). Though
conventional rake receiver provides reasonable performance in the WCDMA downlink system due to path
diversity, but it does not restores the orthogonality. Linear equalizer restores orthogonality and suppresses
MAI, but it is not efficient, since its performance depends on the spectral characteristics of the channel. To
overcome this, Minimum Mean Square Error- Decision Feedback Equalizer (MMSE-DFE) with a linear,
anticausal feedforward filter, causal feedback filter and simple detector is proposed in this paper. The filter taps
of finite length DFE is derived using the cholesky factorization theory, capable of suppressing noise,
Intersymbol Interference (ISI) and MAI. This paper describes the WCDMA downlink system using finite length
MMSE-DFE and takes into consideration the effects of interference which includes additive white gaussian
noise, multipath fading, ISI and MAI. Furthermore, the performance is compared with conventional rake
receiver and MMSE and the simulation results are shown.
Channel and clipping level estimation for ofdm in io t –based networks a reviewIJARIIT
Internet of Things (IoT) is the idea to connect all devices to the internet. To implement such systems, we need to design
low cost and less complex transmitters and make the receiver side complex. Now days OFDM is mainly used for communication
due to its great advantages. But it faces the main problem such as PAPR due to the non-linear performance of High power
amplifiers. There are so many methods are available to reduce the effect of PAPR in OFDM transmission, among this clipping
is the simplest one. In this paper, we propose two algorithms to find the clipping level as well as the channel estimation. The
efficiency of these algorithms is evaluated by using CLRB calculation.
Area efficient parallel LFSR for cyclic redundancy check IJECEIAES
Cyclic Redundancy Check (CRC), code for error detection finds many applications in the field of digital communication, data storage, control system and data compression. CRC encoding operation is carried out by using a Linear Feedback Shift Register (LFSR). Serial implementation of CRC requires more clock cycles which is equal to data message length plus generator polynomial degree but in parallel implementation of CRC one clock cycle is required if a whole data message is applied at a time. In previous work related to parallel LFSR, hardware complexity of the architecture reduced using a technique named state space transformation. This paper presents detailed explaination of search algorithm implementation and technique to find number of XOR gates required for different CRC algorithms. This paper presents a searching algorithm and new technique to find the number of XOR gates required for different CRC algorithms. The comparison between proposed and previous architectures shows that the number of XOR gates are reduced for CRC algorithms which improve the hardware efficiency. Searching algorithm and all the matrix computations have been performed using MATLAB simulations.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Reduction of PAPR and Efficient detection ordering scheme for MIMO Transmissi...IJERA Editor
The technical challenges for communication engineers is the development of best performance wireless
networks with negligible amount of distortions. We have to consider multipath propagation attenuation and
radio spectrum inefficiency. Now a days, In MIMO (Multi Input Multi Output) systems there is a huge demand
for the networks with the high transmission rates and better quality of service which are having low PAPR ratio.
Instead of OFDMA, filter banks are used in massive MIMO to reduce the complexity. But they are error prone
to noise. This base paper discusses about PAPR reduction in MIMO systems using different precoding based
OFDM systems. Mainly, minimization of multi-antenna systems by controlling the transmission power and
reduction of PAPR using ZC (Zadoff-Chu) matrix transform.
Multiuser Detection with Decision-feedback Detectors and PIC in MC-CDMA SystemTELKOMNIKA JOURNAL
In this paper we propose an iterative parallel decision feedback (P-DF) receivers associated with
parallel interference cancellation (PIC) for multicarrier code division multiple access (MC-CDMA) systems
in a Rayleigh fading channel (cost 207). First the most widely detection techniques, minimum
mean-squared error MMSE, Maximum Likelihood ML and PIC were investigated in order to compare their
performances in terms of Bit Error Rate (BER) with parallel feedback detection P-DFD. A MMSE DF
detector that employs parallel decision-feedback (MMSE-P-DFD) is considered and shows almost the
same BER performance with MMSE and ML, which present a better result than the other techniques. In a
second time, an iterative proposed method based on the multi-stage techniques P-DFD
(parallel DFD with two stages) and PIC was exploited to improve the performance of the system.
ICI and PAPR enhancement in MIMO-OFDM system using RNS codingIJECEIAES
The Inter-Carrier-Interference (ICI) is considered a bottleneck in the utilization of Multiple-Input-Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, due to the sensitivity of the OFDM towards frequency offsets which lead to loss of orthogonality, interference and performance degradation. In this paper Residue Numbers as a coding scheme is impeded in MIMO-OFDM systems, where the ICI levels is measured and evaluated with respect to conventional ICI mitigation techniques implemented in MIMO-OFDM. The Carrier-to-Interference Ratio (CIR), the system Bit-Error-Rate (BER) and the Complementary Cumulative Distribution Function (CCDF) for MIMO-OFDM system with Residue Number System (RNS) coding are analyzed and evaluated. The results had demonstrated a performance of transmission model with and without RNS.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Intersymbol interference caused by multipath in band limited frequency selective time dispersive channels distorts the transmitted signal, causing bit error at receiver. ISI is the major obstacle to high speed data transmission over wireless channels. Channel estimation is a technique used to combat the intersymbol interference. The objective of this paper is to improve channel estimation accuracy in MIMO-OFDM system by using modified variable step size leaky Least Mean Square (MVSSLLMS) algorithm proposed for MIMO OFDM System. So we are going to analyze Bit Error Rate for different signal to noise ratio, also compare the proposed scheme with standard LMS channel estimation method.
Multi carrier equalization by restoration of redundanc y (merry) for adaptive...IJNSA Journal
This paper proposes a new blind adaptive channel shortening approach for multi-carrier systems. The
performance of the discrete Fourier transform-DMT (DFT-DMT) system is investigated with the proposed
DST-DMT system over the standard carrier serving area (CSA) loop1. Enhanced bit rates demonstrated
and less complexity also involved by the simulation of the DST-DMT system.
An identification of the tolerable time-interleaved analog-todigital convert...IJECEIAES
High-speed Terahertz communication systems has recently employed orthogonal frequency division multiplexing approach as it provides high spectral efficiency and avoids inter-symbol interference caused by dispersive channels. Such high-speed systems require extremely high-sampling time-interleaved analog-to-digital converters at the receiver. However, timing mismatch of time-interleaved analog-to-digital converters significantly causes system performance degradation. In this paper, to avoid such performance degradation induced by timing mismatch, we theoretically determine maximum tolerable mismatch levels for orthogonal frequency division multiplexing communication systems. To obtain these levels, we first propose an analytical method to derive the bit error rate formula for quadrature and pulse amplitude modulations in Rayleigh fading channels, assuming binary reflected gray code (BRGC) mapping. Further, from the derived bit error rate (BER) expressions, we reveal a threshold of timing mismatch level for which error floors produced by the mismatch will be smaller than a given BER. Simulation results demonstrate that if we preserve mismatch level smaller than 25% of this obtained threshold, the BER performance degradation is smaller than 0.5 dB as compared to the case without timing mismatch.
Low Power Adaptive FIR Filter Based on Distributed ArithmeticIJERA Editor
This paper aims at implementation of a low power adaptive FIR filter based on distributed arithmetic (DA) with
low power, high throughput, and low area. Least Mean Square (LMS) Algorithm is used to update the weight
and decrease the mean square error between the current filter output and the desired response. The pipelined
Distributed Arithmetic table reduces switching activity and hence it reduces power. The power consumption is
reduced by keeping bit-clock used in carry-save accumulation much faster than clock of rest of the operations.
We have implemented it in Quartus II and found that there is a reduction in the total power and the core dynamic
power by 31.31% and 100.24% respectively when compared with the architecture without DA table
Rabid Euclidean direction search algorithm for various adaptive array geometriesjournalBEEI
One of the exciting technologies used to meet the increasing demand for wireless communication services is a smart antenna. A smart antenna is basically confirmed by an array of antennas and a digital beamformer unit through which cellular base station can direct the beam toward the desired user and set nulls toward interfering users. In this paper, different array configurations (linear, circular, and planer) with the REDS algorithm are implemented in the digital beam-forming unit. The wireless system performance is investigated to check the smart antenna potentials assuming Rayleigh fading channel environment beside the AWGN channel. Results show how the REDS algorithm offers a significant improvement through antenna radiation pattern optimization, sidelobe level, and interference reduction, and also the RDES algorithm proves fast convergence with minimum MSE and better sidelobe level reduction comparing with other algorithms.
Multi-carrier Equalization by Restoration of RedundancY (MERRY) for Adaptive ...IJNSA Journal
This paper proposes a new blind adaptive channel shortening approach for multi-carrier systems. The performance of the discrete Fourier transform-DMT (DFT-DMT) system is investigated with the proposed DST-DMT system over the standard carrier serving area (CSA) loop1. Enhanced bit rates demonstrated and less complexity also involved by the simulation of the DST-DMT system.
PERFORMANCE AND COMPLEXITY ANALYSIS OF A REDUCED ITERATIONS LLL ALGORITHMIJCNCJournal
Multiple-input multiple-output (MIMO) systems are playing an increasing and interesting role in the recent
wireless communication. The complexity and the performance of the systems are driving the different
studies and researches. Lattices Reduction techniques bring more resources to investigate the complexity
and performances of such systems.
In this paper, we look to modify a fixed complexity verity of the LLL algorithm to reduce the computation
operations by reducing the number of iterations without important performance degradation. Our proposal
shows that we can achieve a good performance results while avoiding extra iteration that doesn’t bring
much performance.
Performance Analysis of Differential Beamforming in Decentralized NetworksIJECEIAES
This paper proposes and analyzes a novel differential distributed beamforming strategy for decentralized two-way relay networks. In our strategy, the phases of the received signals at all relays are synchronized without requiring channel feedback or training symbols. Bit error rate (BER) expressions of the proposed strategy are provided for coherent and differential M-PSK modulation. Upper bounds, lower bounds, and simple approximations of the BER are also derived. Based on the theoretical and simulated BER performance, the proposed strategy offers a high system performance and low decoding complexity and delay without requiring channel state information at any transmitting or receiving antenna. Furthermore, the simple approximation of the BER upper bound shows that the proposed strategy enjoys the full diversity gain which is equal to the number of transmitting antennas.
A novel delay dictionary design for compressive sensing-based time varying ch...TELKOMNIKA JOURNAL
Compressive sensing (CS) is a new attractive technique adopted for Linear Time Varying channel estimation. orthogonal frequency division multiplexing (OFDM) was proposed to be used in 4G and 5G which supports high data rate requirements. Different pilot aided channel estimation techniques were proposed to better track the channel conditions, which consumes bandwidth, thus, considerable data rate reduced. In order to estimate the channel with minimum number of pilots, compressive sensing CS was proposed to efficiently estimate the channel variations. In this paper, a novel delay dictionary-based CS was designed and simulated to estimate the linear time varying (LTV) channel. The proposed dictionary shows the suitability of estimating the channel impulse response (CIR) with low to moderate Doppler frequency shifts with acceptable bit error rate (BER) performance.
Similar to Discrete-wavelet-transform recursive inverse algorithm using second-order estimation of the autocorrelation matrix (20)
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
In this paper, snake optimization algorithm (SOA) is used to find the optimal gains of an enhanced controller for controlling congestion problem in computer networks. M-file and Simulink platform is adopted to evaluate the response of the active queue management (AQM) system, a comparison with two classical controllers is done, all tuned gains of controllers are obtained using SOA method and the fitness function chose to monitor the system performance is the integral time absolute error (ITAE). Transient analysis and robust analysis is used to show the proposed controller performance, two robustness tests are applied to the AQM system, one is done by varying the size of queue value in different period and the other test is done by changing the number of transmission control protocol (TCP) sessions with a value of ± 20% from its original value. The simulation results reflect a stable and robust behavior and best performance is appeared clearly to achieve the desired queue size without any noise or any transmission problems.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchair’s movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
ResNet-n/DR: Automated diagnosis of diabetic retinopathy using a residual neu...TELKOMNIKA JOURNAL
Diabetic retinopathy (DR) is a progressive eye disease associated with diabetes, resulting in blindness or blurred vision. The risk of vision loss was dramatically decreased with early diagnosis and treatment. Doctors diagnose DR by examining the fundus retinal images to develop lesions associated with the disease. However, this diagnosis is a tedious and challenging task due to growing undiagnosed and untreated DR cases and the variability of retinal changes across disease stages. Manually analyzing the images has become an expensive and time-consuming task, not to mention that training new specialists takes time and requires daily practice. Our work investigates deep learning methods, particularly convolutional neural network (CNN), for DR diagnosis in the disease’s five stages. A pre-trained residual neural network (ResNet-34) was trained and tested for DR. Then, we develop computationally efficient and scalable methods after modifying a ResNet-34 with three additional residual units as a novel ResNet-n/DR. The Asia Pacific Tele-Ophthalmology Society (APTOS) 2019 dataset was used to evaluate the performance of models after applying multiple pre-processing steps to eliminate image noise and improve color contrast, thereby increasing efficiency. Our findings achieved state-of-the-art results compared to previous studies that used the same dataset. It had 90.7% sensitivity, 93.5% accuracy, 98.2% specificity, 89.5% precision, and 90.1% F1 score.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
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• Compatible with IDM8000 CCR.
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Discrete-wavelet-transform recursive inverse algorithm using second-order estimation of the autocorrelation matrix
1. TELKOMNIKA Telecommunication, Computing, Electronics and Control
Vol. 18, No. 6, December 2020, pp. 3073~3079
ISSN: 1693-6930, accredited First Grade by Kemenristekdikti, Decree No: 21/E/KPT/2018
DOI: 10.12928/TELKOMNIKA.v18i6.16191 3073
Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA
Discrete wavelet transform recursive inverse algorithm using
second-order estimation of the autocorrelation matrix
Mohammad Shukri Salman1
, Alaa Eleyan2
, Bahaa Al-Sheikh3
1,3
College of Engineering and Technology, American University of the Middle East, Kuwait
2
Electrical and Electronics Engineering, Ankara Science University, Turkey
Article Info ABSTRACT
Article history:
Received Mar 28, 2020
Revised Jun 17, 2020
Accepted Jul 6, 2020
The recursive least squares (RLS) algorithm was introduced as an alternative
to least mean square (LMS) algorithm with enhanced performance.
Computational complexity and instability in updating the autocolleltion matrix
are some of the drawbacks of the RLS algorithm that were among the reasons
for the introduction of the second-order recursive inverse (RI) adaptive
algorithm. The 2nd
order RI adaptive algorithm suffered from low convergence
rate in certain scenarios that required a relatively small initial step-size. In this
paper, we propose a new second-order RI algorithm that projects the input
signal to a new domain namely discrete wavelet transform (DWT) as pre step
before performing the agorthim. This transformation overcomes the low
convergence rate of the second-order RI algorithm by reducing the self-
correlation of the input signal in the mentioned scenatios. Expeirments are
conducted using the noise cancellation setting. The performance of the
proposed algorithm is compared to those of the RI, original second-order RI
and RLS algorithms in different Gaussian and impulsive noise environments.
Simulations demonstrate the superiority of the proposed algorithm in terms of
convergence rate compared to those algorithms.
Keywords:
Impulsive noise
Noise cancellation
RI algorithm
RLS algorithm
Wavelet transform
This is an open access article under the CC BY-SA license.
Corresponding Author:
Mohammad Shukri Salman,
College of Engineering and Technology,
American University of the Middle East,
+965 2225 1400, ext: 1765, Kuwait.
Email: mohammad.salman@aum.edu.kw
1. INTRODUCTION
Adaptive filtering techniques can promote accurate solutions and high convergence rates in many
signal processing problems [1-3]. Some of these well-known problems; such as, noise cancellation [4, 5],
channel equalization [6], and system identification [7, 8], have been addressed by many researchers for many
decades. The straightforward steps of the least mean square (LMS) adaptive algorithm in weights update
together with its fast convergence (if optimum step-size is selected), made it a very popular filtering algorithm.
However, its convergence rate is easily affected by the spread of the eigenvalue of the autocorrelation matrix
of the tap-input vector [9-13].
The recursive least square (RLS) algorithm [9] was introduced as an alternative to LMS algorithm with
a superior performance. Particularly, in highly correlated environments with the possibility of high eigenvalue
spread of the autocorrelation matrix. However, the RLS algorithm has its own drawbacks such as; high
computational complexity, and updating the inverse autocorrelation matrix that may raise numerical stability
problems [14]. To overcome such problems of the RLS algorithm, many other algorithms have been proposed.
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The recursive inverse (RI) algorithm [15] has been proposed to overcome some of the above
mentioned drawbacks. It has been shown that the RI algorithm performs significantly better than LMS
algorithm and its variants. Also, its performance is very comparable to that of the RLS algorithm, in terms of
convergence rate and excess mean square error (MSE) [16], in various settings, with less computational
complexity. Futher improvement of the performance of the recursive inverse algorithm was achived by
considering second-order estimation of the correlations in the update equation of the RI algorithm [17]. Even
though the second-order RI converges to a lower MSE, its convergence rate is less than those of the RI and
RLS algorithms. This slow convergence is due to second-order estimation of the correlations.
In this paper, we propose the use of discrete wavelet transform (DWT) to improve the performance of
the second-order RI algorithm. This domain-based transformation gurentees the reduction of the self-correlation
of the input signal that, in turn, helps to overcomes the low convergence rate of the second-order RI algorithm.
Hence, we use the advantages of the RI algorithm compared to the RLS algorithm and by the virtue of DWT,
the convergence rate is increased. The rest of the paper can be descried as follows: in section 2, DWT is
reviewed. In section 3, the proposed algorithm is introduced. In section 4, simulation results that compare
the performance of the proposed algorithm to those of the RI, second-order RI and RLS algorithms in different
Gaussian and impulsive noise environments in a noise cancellation setting are presented. Finally, conclusions
are drawn in section 5.
2. DISCRETE WAVELET TRANSFORM (DWT)
Multi-resolution decomposition theory that was developed by Mallat [18], gives scale-invariant
interpretation of signals and images. Wavelet transform is considered to be a powerful approach of
multi-resolution analysis to analyse signals that possess both low and high-frequency components. It has been
developed to solve the time-frequency resolution problem in short time fourier transform (STFT) [19-21].
DWT decomposes the signal into orthogonal set of wavelets using filter banks. The output of the filter banks
is a group of coefficients used to calculate the details and approximations of the signal. Accordingly,
the original signal can be reconstructed from the scaling and the wavelet coefficients. A structure of discrete
wavelet transform adaptive filter (DWTAF) is shown in Figure 1.
According to DWT theory, reconstruction of the original signal x(𝑘) can be performed using
the following finite sum:
x(𝑘) = ∑ ∑ 𝜃𝑗,𝑛 𝜓𝑗,𝑛(𝑘)𝑛∈𝑍
𝐽−1
𝑗=0 (1)
where 𝜃𝑗,𝑛 are the wavelet coefficients and 𝜓𝑗,𝑛(𝑘) are the wavelet functions that form an orthogonal basis.
The purpose of DWT adaptive filter is to generate the discrete reconstruction of x𝑗(𝑘) which is the projected
discrete form of x(𝑘) in wavelet subspace. x𝑗(𝑘) is given by:
x𝑗(𝑘) = ∑ 𝜃𝑗,𝑛 𝜓𝑗,𝑛(𝑘)𝑛∈𝑍 (2)
if v𝑗(𝑘) is the approximation of projected x𝑗(𝑘), then
v𝑗(𝑘) = ∑ 𝜃̂𝑗,𝑛 𝜓𝑗,𝑛(𝑘)𝑛∈𝑍 (3)
where 𝜃̂𝑗,𝑛is the discrete approximation of the wavelet coefficients 𝜃𝑗,𝑛,
𝜃̂𝑗,𝑛 = ∑ x(𝑙) 𝜓̂ 𝑗,𝑛(𝑙)𝑙 (4)
where 𝜓̂ 𝑗,𝑛(𝑙) represents the discrete approximation of the wavelet functions 𝜓𝑗,𝑛(𝑙) given that,
ℎ𝑗(𝑙, 𝑘) = ∑ 𝜓̂ 𝑗,𝑛(𝑙) 𝜓𝑗,𝑛(𝑘)𝑛∈𝑍 (5)
Now, substituting (4) and (5) in (3) results in
v𝑗(𝑘) = ∑ x(𝑙) ℎ𝑗(𝑙, 𝑘)𝑙 (6)
In (6) is simply the discrete convolution of the input signal x(𝑘) and the filter coefficients ℎ𝑗(𝑙, 𝑘). Using
orthogonality and time-steadiness, filter indices can be rewritten as:
ℎ𝑗(𝑙, 𝑘) = ℎ𝑗(𝑙 − 𝑘) (7)
3. TELKOMNIKA Telecommun Comput El Control
Discrete wavelet transform recursive inverse algorithm using second-order… (Mohammad Shukri Salman)
3075
Therefore,
v𝑗(𝑘) = ∑ x(𝑙) ℎ𝑗(𝑙 − 𝑘)𝑙 (8)
3. DWT SECOND-ORDER RECURSIVE INVERSE ALGORITHM
Following the structure shown in Figure 1 and using the same notation used in section 2, the updated
equation of the second-order RI algorithm [17] can be written as:
C(𝑘 + 1) = ⌈I − 𝜇(𝑘)R(𝑘)⌉C(𝑘) + 𝜇(𝑘)p(𝑘) (9)
where 𝑘 is the time parameter (𝑘 = 1, 2, . . . ), C(𝑘) represents the filter weight vector calculated at time
𝑘, v(𝑘) = Wx(𝑘) represents the transformed input signal and W represents the wavelet transform matrix of
size 𝐽 × 𝑁. 𝜇(𝑘) represents the variable step-size [16] which satisfies the convergence criterion [9],
the autocorrelation matrix R(𝑘) represents the estimate of the tap-input vector, and p(𝑘) represents the estimate
of the cross-correlation vector between the desired output signal 𝑑(𝑘) and the tap-input vector estimated,
recursively, as:
R(𝑘) = 𝛽1R(𝑘 − 1) + 𝛽2R(𝑘 − 2) + v(𝑘) v 𝑇
(𝑘) (10)
p(𝑘) = 𝛽1p(𝑘 − 1) + 𝛽2p(𝑘 − 2) + 𝑑(𝑘) v(𝑘) (11)
where 𝛽1 and 𝛽2 are positive constants. Choosing the coefficients in (10) and (11) to be equal, i.e. 𝛽1 = 𝛽2 =
1
2
𝛽,
will gurentee that the The number of multiplications in the second order update equations will be the same as
the first order update equations [16].
By taking the expectation of (10), the new equation can be written as:
R̅(𝑘) =
1
2
𝛽R̅(𝑘 − 1) +
1
2
𝛽R̅(𝑘 − 2) + 𝑅 𝑣𝑣 (12)
where Rvv = 𝐸{ v(𝑘) v 𝑇
(𝑘)} and R̅(𝑘) = 𝐸{R(𝑘)}. The poles of the system in (12) can be calcutaed using:
𝑧1 =
1
4
(𝛽 − √𝛽2 + 8𝛽)
𝑧2 =
1
4
(𝛽 + √𝛽2 + 8𝛽)
(13)
which have magnitudes less than unity if 𝛽 < 1. By solving (12) using the initial conditions
R̅(−2) = R̅ (−1) = R̅(0) = 0, it results in,
R̅(𝑘) = (
1
𝛽−1
+ 𝛼1 𝑧1
𝑘
+ 𝛼2 𝑧2
𝑘
) Rvv (14)
where,
𝛼1 =
𝛽−𝑧2
(1−𝛽)(𝑧2−𝑧1)
,
𝛼2 =
𝛽−𝑧1
(1−𝛽)(𝑧2−𝑧1)
.
(15)
using,
𝛾(𝑘) =
1
𝛽−1
+ 𝛼1 𝑧1
𝑘
+ 𝛼2 𝑧2
𝑘
(16)
then, in the DWT second-order RI algorithm, the variable step-size is selected as:
𝜇(𝑘) =
𝜇0
𝛾(𝑘)
, (17)
where 𝜇0 is a constant [16] selected as:
𝜇0 < 𝜇 𝑚𝑎𝑥 =
2(1−𝛽)
𝜆 𝑚𝑎𝑥 Rvv
where 𝜆 𝑚𝑎𝑥 is the maximum eigenvalue of Rvv.
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The adaptive estimation error can be defined as:
𝑒(𝑘) = 𝑑(𝑘) − 𝑦(𝑘) (18)
where,
𝑦(𝑘) = v 𝑇
(𝑘)C(𝑘) = ∑ 𝑣𝑗 (𝑘)𝑐𝑗(𝑘) = ∑ ∑ 𝑐𝑗(𝑘) ℎ𝑗(𝑙 − 𝑘) 𝑥(𝑙)𝑙 .𝐽−1
𝑗=0
𝐽−1
𝑗=0 (19)
The major advantage of RI-based algorithms over the RLS-based algorithm is the unnecessity to update the inverse
autocorrelation matrix [16]. Such an update of the inverse autocorrelation matrix might cuase numerical instabilities
in RLS-based algorithms [22-24]. Fortunately, this is not the case for the RI algorithm and its variants.
Figure 1. Structure of discrete wavelet transform transversal adaptive filter
4. SIMULATION RESULTS
The proposed algorithm is compared to the RI, second-order RI and RLS algorithms in the noise
cancellation setting as shown in Figure 2 in terms of convergence rate and mean square error (MSE). In all
conducted expeirments, filter length for all implemenetd algorithms was equal to 16 taps and SNR = 30 dB.
The received signal is generated using:
𝑥𝑖(𝑘) = 1.79𝑥𝑖(𝑘 − 1) − 1.85𝑥𝑖(𝑘 − 2) + 1.27𝑥𝑖(𝑘 − 3) − 0.41𝑥𝑖(𝑘 − 4) + 𝑛0(𝑘),
where 𝑛0(𝑘) is a Gaussian process with zero mean and variance 𝜎2
= 0.15. The simulation results for
Gaussian and impulsive noise are obtained by averaging 1000 independent runs. For all experiments,
the algorithms are simulated using the parameters in Table 1.
Figure 2. Block diagram of adaptive noise cancellation configuration
Table 1. Parameters used for simulating the proposed, 2nd
order RI, RI and RLS algorithms in all experiments
Algorithm 𝜇0 𝛽
Proposed 0.1 0.99
2nd
order RI 0.1 0.99
RI 0.0005 0. 99
RLS - 0.99
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Discrete wavelet transform recursive inverse algorithm using second-order… (Mohammad Shukri Salman)
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4.1. Additive Gaussian noise
In order to test the performance of the proposed algorithm, the signal is assumed to be distorted with an
additive white/correlated Gaussian noise (AWGN/ACGN) process. The correlated noise is created using AR(1)
process (𝑁0(𝑘 + 1) = 0.7𝑁0(𝑘) + 𝑣(𝑘)) where 𝑣(𝑘) respresents a white Gaussian process with mean equals
to zero and a variance that maintains a 30 dB SNR. From Figure 3 and Figure 4, it can be seen that the proposed
algorithm converges to same MSE (MSE = −30 dB) of all algorithms with faster convergence rate (approximately
170, 350 and 850 iterations faster than the RLS, 2nd
order RI and RI algorithms, respectively).
4.2. Additive impulsive noise
Man-made noise, such as underwater acoustic noise, added to the received signal makes it hard to
model the signal using Gaussian distribution. To over come this problem, such type of noise is believed to
better modelled using a Gaussian mixture model. The impulsive noise process is generated by the probability
density function [25]. 𝑝 = (1 − 𝜁)𝐺(0, 𝜎2) + 𝜁𝐺(0, 𝜅𝜎2
) with variance 𝜎 𝑝
2
= (1 − 𝜁)𝜎2
+ 𝜁𝜅𝜎2
where
𝐺(0, 𝜎2) is a Gaussian probability density function with zero mean and variance 𝜎2
that represents the nominal
background noise. 𝐺(0, 𝜅𝜎2
) represents the impulsive component of the noise model, where 𝜁 is the probability
and 𝜅 ≥ 1 is the strength of the impulsive noise components, respectively.
In order to test the robustness of the proposed algorithm, and to study the effects of the impulsive
components (outliers) of the noise process in the noise cancellation setting, an impulsive noise process is
generated by the aforementioned probability density function with 𝜁 = 0.2 and 𝜅 = 100. Firstly, the signal
is assumed to be distorted by an additive white impulsive noise (AWIN) process. Then, the same experiment
is repeated while assuming the signal is corrupted by a correlated impulsive noise created using
the aforementionedAR(1). In both Figures 5 and 6 it can be seen that the proposed algorithm converges to
same MSE (MSE = −30 dB) of the 2nd
order RI and RI algorithms with faster conver-gence rate (approximately
400 and 600 iterations faster than 2nd
order RI and RI algorithms, respectively). In addition, it is noted that
even though the RLS tries to converge at the beginning, it starts to slowly diverge after almost 800 iterations.
Figure 3. The ensemble MSE for the proposed, RI,
2nd order RI and RLS algorithms in AWGN
Figure 4. The ensemble MSE for the proposed, RI,
2nd order RI and RLS algorithms in ACGN
Figure 5. The ensemble MSE for the proposed, RI,
2nd order RI and RLS algorithms in AWIN
Figure 6. The ensemble MSE for the proposed, RI,
2nd order RI and RLS algorithms in ACIN
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5. CONCLUSIONS
In this paper, a new domain transform based second-order RI algorithm was proposed. Applying DWT at
the input signal has highly improved the performance of the original second-order RI algorithm. The performance
of the proposed algorithm was evaluated using noise cancellation setting. It was compared to those of the RI, 2nd
order RI and RLS algorithms in different Gaussian and impulsive noise environments. Condcuted experiments
demonestrated that the proposed algorithm has superior convergence rate compared to those algorithms.
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BIOGRAPHIES OF AUTHORS
Mohammad Shukri Salman received the B.Sc., M.Sc. and Ph.D. Degrees in Electrical and
Electronics Engineering from Eastern Mediterranean University (EMU), in 2006, 2007 and
2011, respectively. From 2006 to 2010, he was a teaching assistant of Electrical and
Electronics Engineering department at EMU. In 2010, he has joined the Department of
Electrical and Electronic Engineering at European University of Lefke (EUL) as a senior
lecturer. For the period 2011-2015, he has worked as an Assist. Prof. in the Department of
Electrical and Electronics Engineering, Mevlana (Rumi) University, Turkey. Currently, he
is an Assoc. Prof. with the Electrical Engineering Department at the American University of
Middle East in Kuwait. He has served as a general chair, program chair and a TPC member
for many international conferences. His research interests include signal processing,
adaptive filters, image processing, sparse representation of signals, control systems and
communications systems.
Alaa Eleyan received the B.Sc. and M.Sc. degrees in Electrical Electronics Engineering
from Near East University, Northern Cyprus, in 2002 and 2004, respectively. In 2009, He
finished his PhD degree in Electrical and Electronics Engineering from Eastern
Mediterranean University, Northern Cyprus. Dr. Eleyan has nearly two decades of working
experience in different universities at Northern Cyprus and Turkey. Currently, he is working
as an associate professor at Ankara Science University, Turkey. His current research
interests are computer vision, signal & image processing, pattern recognition, machine
learning and robotics. He has more than 60 published journal articles and conference papers
in these research fields. Dr. Eleyan served as general chair of many international conferences
such as ICDIPC2019, DIPECC2018, TAEECE2018 and DICTAP2016.
Bahaa Al-Sheikh received the B.Sc. degree in Electronics Engineering from Yarmouk
University, Jordan, MSc in Electrical Engineering from Colorado State University,
Colorado, USA, and PhD in Biomedical Engineering degree from the University of Denver,
Colorado, USA, in 2000, 2005 and 2009, respectively. Between 2009 and 2015, he worked
for Yarmouk University as an assistant professor in the department of Biomedical Systems
and Medical Informatics Engineering and served as the department chairman between 2010
and 2012. He served as a part-time consultant for Sand-hill Scientific Inc., Highlands Ranch,
Colorado, USA in Biomedical Signal Processing field between 2009 and 2014. Currently,
he is an Associate Professor at the Electrical Engineering Department at the American
University of the Middle East in Kuwait. His research interests include digital signal and
image processing, biomedical systems modeling, medical instrumentation and sound source
localization systems.