This document reviews various techniques for analyzing music, including extracting and recognizing musical instruments, estimating pitch and tempo, and extracting and recognizing musical notes. It discusses using matrix factorization techniques like non-negative matrix factorization (NMF) and its variants to separate music into instrumental tracks. It also reviews using neural networks with different features to recognize instruments. Other techniques discussed are using the continuous wavelet transform (CWT) to capture timbre characteristics and linear discriminant analysis (LDA) for classification. It discusses various pitch estimation methods like autocorrelation, average magnitude difference function, and linear predictive coding. It also reviews approaches for tempo estimation and extracting and recognizing musical notes.
Chebyshev filter applied to an inversion technique for breast tumour detectioneSAT Journals
Abstract Microwave imaging has been extensively studied in the past several years as a new technique for early stage breast cancer detection. The rationale of microwave imaging for breast tumour detection is significant contrast in the dielectric properties of normal tissue and malignant tumours. However, in practice noise present from the environments during screening/examination degrades the quality of the image. Inaccurate reconstructed image caused false/misleading interpretation of the image which leads to inappropriate diagnose or treatment to the patient. In the simulation works, noise is added to imitate the actual environment scenario. The two-dimensional (2D) object that identical to breast model is developed using numerical simulation to imitate the breast model. A filter is integrated with an iterative inversion technique for breast tumour detection to eliminate the noise. To assess the effectiveness of this approach, we consider the reconstruction of the electrical parameter profiles of 2D objects from measurements of the transient total electromagnetic field data contaminated with noise. Additive white Gaussian noise is utilized to mimic the effect of random processes that occur in the nature. This paper presents the filter settings and characteristics that affect the reconstruction of the image in order to obtain the most reliable and closer to the actual image. Selection of filter settings or design is important in order to achieve desired signal, most accurate image and provide reliable information of the object. Chebyshev low pass filter is applied in the Forward-Backward Time-Stepping (FBTS) algorithm to filter the noisy data and to improve the quality of reconstructed image. Keywords: Chebyshev low pass filter, microwave imaging and breast tumour detection
Radio Signal Classification with Deep Neural NetworksKachi Odoemene
6th place solution to 2018 Army Signal Classification Challenge.
Radio Signal Modulation Recognition.
Competition hosted by Army Rapid Capabilities Office and MITRE.
Performance Analysis of Adaptive DOA Estimation Algorithms For Mobile Applica...IJERA Editor
Spatial filtering for mobile communications has attracted a lot of attention over the last decade and is cur-rently considered a very promising technique that will help future cellular networks achieve their ambi-tious goals. One way to accomplish this is via array signal processing with algorithms which estimate the Direction-Of-Arrival (DOA) of the received waves from the mobile users. This paper evaluates the per-formance of a number of DOA estimation algorithms. In all cases a linear antenna array at the base station is assumed to be operating typical cellular environment.
A Combined Voice Activity Detector Based On Singular Value Decomposition and ...CSCJournals
voice activity detector (VAD) is used to separate the speech data included parts from silence parts of the signal. In this paper a new VAD algorithm is represented on the basis of singular value decomposition. There are two sections to perform the feature vector extraction. In first section voiced frames are separated from unvoiced and silence frames. In second section unvoiced frames are silence frames. To perform the above sections, first, windowing the noisy signal then Hankel’s matrix is formed for each frame. The basis of statistical feature extraction of purposed system is slope of singular value curve related to each frame by using linear regression. It is shown that the slope of singular values curve per different SNRs in voiced frames is more than the other types and this property can be to achieve the goal the first part can be used. High similarity between feature vector of unvoiced and silence frame caused to approach for separation of the two categories above cannot be used. So in the second part, the frequency characteristics for identification of unvoiced frames from silent frames have been used. Simulation results show that high speed and accuracy are the advantages of the proposed system.
Expert system design for elastic scattering neutrons optical model using bpnnijcsa
In present paper, a proposed expert system is designed to obtain a trained formulae for the optical model
parameters used in elastic scattering neutrons of light nuclei for (7Li), at energy range between [(1) to
(20)] MeV. A simple algorithm has used to design this expert system, while a multi-layer backwardpropagation
neural network (BPNN) is applied for training and testing the data used in this model. This
group of formulae may get a simple expert system occurring from governing formulae model, and predicts
the critical parameters usually resulted from the complicated computer coding methods. This expert system
may use in nuclear reactions yields in both fission and fusion nature who gives more closely results to the
real model.
Reducting Power Dissipation in Fir Filter: an AnalysisCSCJournals
In this paper, three existing techniques, Signed Power-of-Two (SPT), Steepest decent and Coefficient segmentation, for power reduction of FIR filters are analyzed. These techniques reduce switching activity which is directly related to the power consumption of a circuit. In an FIR filter, the multiplier consumes maximum power. Therefore, power consumption can be reduced either by by making the filter multiplier-less or by minimizing hamming distance between the coefficients of this multiplier as it directly translates into reduction in power dissipation [8]. The results obtained on four filters (LP) show that hamming distance can be reduced upto 26% and 47% in steepest decent and coefficient segmentation algorithm respectively. Multiplier-less filter can be realized by realizing coefficients in signed power-of-two terms, i.e. by shifting and adding the coefficients, though at the cost of shift operation overhead.
Chebyshev filter applied to an inversion technique for breast tumour detectioneSAT Journals
Abstract Microwave imaging has been extensively studied in the past several years as a new technique for early stage breast cancer detection. The rationale of microwave imaging for breast tumour detection is significant contrast in the dielectric properties of normal tissue and malignant tumours. However, in practice noise present from the environments during screening/examination degrades the quality of the image. Inaccurate reconstructed image caused false/misleading interpretation of the image which leads to inappropriate diagnose or treatment to the patient. In the simulation works, noise is added to imitate the actual environment scenario. The two-dimensional (2D) object that identical to breast model is developed using numerical simulation to imitate the breast model. A filter is integrated with an iterative inversion technique for breast tumour detection to eliminate the noise. To assess the effectiveness of this approach, we consider the reconstruction of the electrical parameter profiles of 2D objects from measurements of the transient total electromagnetic field data contaminated with noise. Additive white Gaussian noise is utilized to mimic the effect of random processes that occur in the nature. This paper presents the filter settings and characteristics that affect the reconstruction of the image in order to obtain the most reliable and closer to the actual image. Selection of filter settings or design is important in order to achieve desired signal, most accurate image and provide reliable information of the object. Chebyshev low pass filter is applied in the Forward-Backward Time-Stepping (FBTS) algorithm to filter the noisy data and to improve the quality of reconstructed image. Keywords: Chebyshev low pass filter, microwave imaging and breast tumour detection
Radio Signal Classification with Deep Neural NetworksKachi Odoemene
6th place solution to 2018 Army Signal Classification Challenge.
Radio Signal Modulation Recognition.
Competition hosted by Army Rapid Capabilities Office and MITRE.
Performance Analysis of Adaptive DOA Estimation Algorithms For Mobile Applica...IJERA Editor
Spatial filtering for mobile communications has attracted a lot of attention over the last decade and is cur-rently considered a very promising technique that will help future cellular networks achieve their ambi-tious goals. One way to accomplish this is via array signal processing with algorithms which estimate the Direction-Of-Arrival (DOA) of the received waves from the mobile users. This paper evaluates the per-formance of a number of DOA estimation algorithms. In all cases a linear antenna array at the base station is assumed to be operating typical cellular environment.
A Combined Voice Activity Detector Based On Singular Value Decomposition and ...CSCJournals
voice activity detector (VAD) is used to separate the speech data included parts from silence parts of the signal. In this paper a new VAD algorithm is represented on the basis of singular value decomposition. There are two sections to perform the feature vector extraction. In first section voiced frames are separated from unvoiced and silence frames. In second section unvoiced frames are silence frames. To perform the above sections, first, windowing the noisy signal then Hankel’s matrix is formed for each frame. The basis of statistical feature extraction of purposed system is slope of singular value curve related to each frame by using linear regression. It is shown that the slope of singular values curve per different SNRs in voiced frames is more than the other types and this property can be to achieve the goal the first part can be used. High similarity between feature vector of unvoiced and silence frame caused to approach for separation of the two categories above cannot be used. So in the second part, the frequency characteristics for identification of unvoiced frames from silent frames have been used. Simulation results show that high speed and accuracy are the advantages of the proposed system.
Expert system design for elastic scattering neutrons optical model using bpnnijcsa
In present paper, a proposed expert system is designed to obtain a trained formulae for the optical model
parameters used in elastic scattering neutrons of light nuclei for (7Li), at energy range between [(1) to
(20)] MeV. A simple algorithm has used to design this expert system, while a multi-layer backwardpropagation
neural network (BPNN) is applied for training and testing the data used in this model. This
group of formulae may get a simple expert system occurring from governing formulae model, and predicts
the critical parameters usually resulted from the complicated computer coding methods. This expert system
may use in nuclear reactions yields in both fission and fusion nature who gives more closely results to the
real model.
Reducting Power Dissipation in Fir Filter: an AnalysisCSCJournals
In this paper, three existing techniques, Signed Power-of-Two (SPT), Steepest decent and Coefficient segmentation, for power reduction of FIR filters are analyzed. These techniques reduce switching activity which is directly related to the power consumption of a circuit. In an FIR filter, the multiplier consumes maximum power. Therefore, power consumption can be reduced either by by making the filter multiplier-less or by minimizing hamming distance between the coefficients of this multiplier as it directly translates into reduction in power dissipation [8]. The results obtained on four filters (LP) show that hamming distance can be reduced upto 26% and 47% in steepest decent and coefficient segmentation algorithm respectively. Multiplier-less filter can be realized by realizing coefficients in signed power-of-two terms, i.e. by shifting and adding the coefficients, though at the cost of shift operation overhead.
Signal Processing and Soft Computing Techniques for Single and Multiple Power...idescitation
In this paper review of various methods and
approaches that are used for the detection and classification
of power quality (PQ) events are presented. Survey has been
divided into two main categories one in which only single
events are considered and another in which combined events
are considered. Table has been also designed to present the
comparative analysis of some references. Application of
wavelet, need of power quality indices and optimization
techniques has been also described in the paper. The aim of
this paper is to show the Performance of various methodologies
so that appropriate technique would be used for the detection
and classification of PQ events.
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.
Signal classification of second order cyclostationarity signals using bt scld...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Direction of Arrival Estimation Based on MUSIC Algorithm Using Uniform and No...IJERA Editor
In signal processing, the direction of arrival (DOA) estimation denotes the direction from which a propagating wave arrives at a point, where a set of antennas is located. Using the array antenna has an advantage over the single antenna in achieving an improved performance by applying Multiple Signal Classification (MUSIC) algorithm. This paper focuses on estimating the DOA using uniform linear array (ULA) and non-uniform linear array (NLA)of antennas to analyze the performance factors that affect the accuracy and resolution of the system based on MUSIC algorithm. The direction of arrival estimation is simulated on a MATLAB platform with a set of input parameters such as array elements, signal to noise ratio, number of snapshots and number of signal sources. An extensive simulation has been conducted and the results show that the NLA with DOA estimation for co-prime array can achieve an accurate and efficient DOA estimation
Voltage variations identification using Gabor Transform and rule-based classi...IJECEIAES
This paper presents a comparatively contemporary easy to use technique for the identification and classification of voltage variations. The technique was established based on the Gabor Transform and the rule-based classification method. The technique was tested by using mathematical model of Power Quality (PQ) disturbances based on the IEEE Std 519-2009. The PQ disturbances focused were the voltage variations, which included voltage sag, swell and interruption. A total of 80 signals were simulated from the mathematical model in MATLAB and used in this study. The signals were analyzed by using Gabor Transform and the signal pattern, timefrequency representation (TFR) and root-mean-square voltage graph were presented in this paper. The features of the analysis were extracted, and rules were implemented in rule-based classification to identify and classify the voltage variation accordingly. The results showed that this method is easy to be used and has good accuracy in classifying the voltage variation.
A mobile ad-hoc network (MANET) is a self structured infrastructure less network of mobile devices
connected by wireless. Each device in a MANET is free to move independently in any direction, and will
therefore change its links to other devices frequently. Load balancing is a technique to share out workload
across network links, to achieve maximize throughput, minimize response time, and avoid overload. Load
imbalance is a one of the critical issue in the ad-hoc network. Particle Swarm Optimization (PSO) method
is used to implement our proposed technique. In this Paper two algorithms are used for balancing the
nodes in the network. Identify the unfair nodes location next allocate and balance the load between the
nodes in the network. The simulation results show that this approach is more effective in terms of packet
delivery ratio, average end-to-end delay, load distribution, packet delay variation, packet reordering, and
throughput.
A Wireless Sensor Network (WSN) is an autonomous and self-organizing network without any pre-established
infrastructure which offers many advantages in military applications and emergency areas. Source Localization is one of the important monitoring tasks of the WSN. It provides the accurate position of the source using various positioning technologies. In this paper an Impulse Radio Ultra wideband (IR-UWB) positioning system with a two-antenna receiver is used to estimate the Time of arrival (TOA) and Direction of arrival (DOA) positioning parameters. A two dimensional (2D) multiple signal classification (MUSIC) algorithm is used to estimate these parameters but it has much higher computational
complexity and also requires 2D spectral peak search. A Successive Multiple signal classification (MUSIC) algorithm is proposed in this paper which estimates the parameters jointly and gets paired automatically. It avoids the two dimensional peak searches and reduces the complexity compared to the existing methods 2D-MUSIC, Root-MUSIC, Matrix Pencil algorithm, Propagator method and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm.
Keywords--Time of arrival (TOA), Direction of arrival (DOA), Impulse Radio Ultra Wideband (IR-UWB), Multiple
Signal Classification (MUSIC).
A SEMI BLIND CHANNEL ESTIMATION METHOD BASED ON HYBRID NEURAL NETWORKS FOR UP...ijwmn
The paper describes how to improve channel estimation in Single Carrier Frequency Division Multiple
Access (SC-FDMA) system, using a Hybrid Artificial Neural Networks (HANN). The 3rd Generation
Partnership Project (3GPP) standards for uplink Long Term Evolution Advanced (LTE-A) uses pilot based
channel estimation technique. This kind of channel estimation method suffers from a considerable loss
ofbitrate due to pilot insertion; all data frame sent contains reference signal. The HANN converts data
aided channel estimator to semi blind channel estimator. To increase convergence speed, HANN uses some
channel propagation Fuzzy Rules to initialize Neural Network parameters before learning instead of a
random initialization, so its learning phase ismore rapidly compared to classic ANN.HANN allows more
bandwidth efficient and less complexity. Simulation results show that HANN has better computational
efficiency than the Minimum Mean Square Error (MMSE) estimator and has faster convergence than
classic Neural Networks estimators.
All optical network design with even and odd nodeseSAT Journals
Abstract
We have studied the effects of OLTs and OADMs in WDM optical networks. All optical networks have proved to be cost efficient
and power saving in comparison to O-E-O networks. Cost of a network can further be reduced by minimizing the number of IP
router ports and the number of wavelengths required. It has been already studied the number of IP router ports required per node
and number of wavelengths required to carry a fixed amount of traffic, considering the network containing even and odd number
of routing nodes. And finally the result has been compared with other architectures like point to point WDM and hub networks,
finally all-optical networks proved to be most cost efficient in saving number of wavelength requirements and IP router port
requirements. In this paper we have compared all-optical network with itself, by taking even and odd number of nodes. That is we
have compared all-optical network containing even number of nodes with the same all-optical network containing odd number of
nodes. The result what we obtained is to honor same amount of traffic “t”, all-optical network containing odd number of nodes
require lesser number of wavelengths than its previous even number of nodes. We have here varied the number of nodes keeping
the amount of traffic fixed assuming static routing for simplicity of our work. Finally we observed the percentage of change in
wavelength requirements decreases on increasing number of nodes. That is for a large network number of wavelength
requirements are large for even number of nodes than odd number of nodes. But this difference is little more for a small network
size.
Keywords: Wavelength Division Multiplexing (WDM), PPWDM (Point to point WDM), Light paths, traffic, alloptical,
Erlang(E).
Signal Processing and Soft Computing Techniques for Single and Multiple Power...idescitation
In this paper review of various methods and
approaches that are used for the detection and classification
of power quality (PQ) events are presented. Survey has been
divided into two main categories one in which only single
events are considered and another in which combined events
are considered. Table has been also designed to present the
comparative analysis of some references. Application of
wavelet, need of power quality indices and optimization
techniques has been also described in the paper. The aim of
this paper is to show the Performance of various methodologies
so that appropriate technique would be used for the detection
and classification of PQ events.
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.
Signal classification of second order cyclostationarity signals using bt scld...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Direction of Arrival Estimation Based on MUSIC Algorithm Using Uniform and No...IJERA Editor
In signal processing, the direction of arrival (DOA) estimation denotes the direction from which a propagating wave arrives at a point, where a set of antennas is located. Using the array antenna has an advantage over the single antenna in achieving an improved performance by applying Multiple Signal Classification (MUSIC) algorithm. This paper focuses on estimating the DOA using uniform linear array (ULA) and non-uniform linear array (NLA)of antennas to analyze the performance factors that affect the accuracy and resolution of the system based on MUSIC algorithm. The direction of arrival estimation is simulated on a MATLAB platform with a set of input parameters such as array elements, signal to noise ratio, number of snapshots and number of signal sources. An extensive simulation has been conducted and the results show that the NLA with DOA estimation for co-prime array can achieve an accurate and efficient DOA estimation
Voltage variations identification using Gabor Transform and rule-based classi...IJECEIAES
This paper presents a comparatively contemporary easy to use technique for the identification and classification of voltage variations. The technique was established based on the Gabor Transform and the rule-based classification method. The technique was tested by using mathematical model of Power Quality (PQ) disturbances based on the IEEE Std 519-2009. The PQ disturbances focused were the voltage variations, which included voltage sag, swell and interruption. A total of 80 signals were simulated from the mathematical model in MATLAB and used in this study. The signals were analyzed by using Gabor Transform and the signal pattern, timefrequency representation (TFR) and root-mean-square voltage graph were presented in this paper. The features of the analysis were extracted, and rules were implemented in rule-based classification to identify and classify the voltage variation accordingly. The results showed that this method is easy to be used and has good accuracy in classifying the voltage variation.
A mobile ad-hoc network (MANET) is a self structured infrastructure less network of mobile devices
connected by wireless. Each device in a MANET is free to move independently in any direction, and will
therefore change its links to other devices frequently. Load balancing is a technique to share out workload
across network links, to achieve maximize throughput, minimize response time, and avoid overload. Load
imbalance is a one of the critical issue in the ad-hoc network. Particle Swarm Optimization (PSO) method
is used to implement our proposed technique. In this Paper two algorithms are used for balancing the
nodes in the network. Identify the unfair nodes location next allocate and balance the load between the
nodes in the network. The simulation results show that this approach is more effective in terms of packet
delivery ratio, average end-to-end delay, load distribution, packet delay variation, packet reordering, and
throughput.
A Wireless Sensor Network (WSN) is an autonomous and self-organizing network without any pre-established
infrastructure which offers many advantages in military applications and emergency areas. Source Localization is one of the important monitoring tasks of the WSN. It provides the accurate position of the source using various positioning technologies. In this paper an Impulse Radio Ultra wideband (IR-UWB) positioning system with a two-antenna receiver is used to estimate the Time of arrival (TOA) and Direction of arrival (DOA) positioning parameters. A two dimensional (2D) multiple signal classification (MUSIC) algorithm is used to estimate these parameters but it has much higher computational
complexity and also requires 2D spectral peak search. A Successive Multiple signal classification (MUSIC) algorithm is proposed in this paper which estimates the parameters jointly and gets paired automatically. It avoids the two dimensional peak searches and reduces the complexity compared to the existing methods 2D-MUSIC, Root-MUSIC, Matrix Pencil algorithm, Propagator method and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm.
Keywords--Time of arrival (TOA), Direction of arrival (DOA), Impulse Radio Ultra Wideband (IR-UWB), Multiple
Signal Classification (MUSIC).
A SEMI BLIND CHANNEL ESTIMATION METHOD BASED ON HYBRID NEURAL NETWORKS FOR UP...ijwmn
The paper describes how to improve channel estimation in Single Carrier Frequency Division Multiple
Access (SC-FDMA) system, using a Hybrid Artificial Neural Networks (HANN). The 3rd Generation
Partnership Project (3GPP) standards for uplink Long Term Evolution Advanced (LTE-A) uses pilot based
channel estimation technique. This kind of channel estimation method suffers from a considerable loss
ofbitrate due to pilot insertion; all data frame sent contains reference signal. The HANN converts data
aided channel estimator to semi blind channel estimator. To increase convergence speed, HANN uses some
channel propagation Fuzzy Rules to initialize Neural Network parameters before learning instead of a
random initialization, so its learning phase ismore rapidly compared to classic ANN.HANN allows more
bandwidth efficient and less complexity. Simulation results show that HANN has better computational
efficiency than the Minimum Mean Square Error (MMSE) estimator and has faster convergence than
classic Neural Networks estimators.
All optical network design with even and odd nodeseSAT Journals
Abstract
We have studied the effects of OLTs and OADMs in WDM optical networks. All optical networks have proved to be cost efficient
and power saving in comparison to O-E-O networks. Cost of a network can further be reduced by minimizing the number of IP
router ports and the number of wavelengths required. It has been already studied the number of IP router ports required per node
and number of wavelengths required to carry a fixed amount of traffic, considering the network containing even and odd number
of routing nodes. And finally the result has been compared with other architectures like point to point WDM and hub networks,
finally all-optical networks proved to be most cost efficient in saving number of wavelength requirements and IP router port
requirements. In this paper we have compared all-optical network with itself, by taking even and odd number of nodes. That is we
have compared all-optical network containing even number of nodes with the same all-optical network containing odd number of
nodes. The result what we obtained is to honor same amount of traffic “t”, all-optical network containing odd number of nodes
require lesser number of wavelengths than its previous even number of nodes. We have here varied the number of nodes keeping
the amount of traffic fixed assuming static routing for simplicity of our work. Finally we observed the percentage of change in
wavelength requirements decreases on increasing number of nodes. That is for a large network number of wavelength
requirements are large for even number of nodes than odd number of nodes. But this difference is little more for a small network
size.
Keywords: Wavelength Division Multiplexing (WDM), PPWDM (Point to point WDM), Light paths, traffic, alloptical,
Erlang(E).
Vibration analysis of laminated composite beam based on virtual instrumentati...Husain Mehdi
Vibration response and its analysis is quite significant in understanding the behavior of a system. Vibrating systems produce complex time series waveforms which consist of many specific trends. These trends need to be properly extracted in order to develop methodologies for detecting system faults, its maintenance and vibration control. In the present analysis a laminated composite beam (Nylon sandwiched between Aluminum) in cantilever configuration is taken as the system model. LabVIEW is used to carry out various analyses from a range of algorithms such as standard frequency analysis, time-frequency analysis for time varying sound and vibration signals, quefrency analysis (FFT of the log of a vibration spectrum) for detecting harmonics, wavelet analysis and model based analysis for transient detection. Results of these algorithms are presented giving information for proper analysis and monitoring of the system model.
Cyclostationary analysis of polytime coded signals for lpi radarseSAT Journals
Abstract In Radars, an electromagnetic waveform will be sent, and an echo of the same signal will be received by the receiver. From this received signal, by extracting various parameters such as round trip delay, doppler frequency it is possible to find distance, speed, altitude, etc. However, nowadays as the technology increases, intruders are intercepting transmitted signal as it reaches them, and they will be extracting the characteristics and trying to modify them. So there is a need to develop a system whose signal cannot be identified by no cooperative intercept receivers. That is why LPI radars came into existence. In this paper a brief discussion on LPI radar and its modulation (Polytime code (PT1)), detection (Cyclostationary (DFSM & FAM) techniques such as DFSM, FAM are presented and compared with respect to computational complexity.
Keywords—LPI Radar, Polytime codes, Cyclostationary DFSM, and FAM
Fault detection and diagnosis ingears using wavelet enveloped power spectrum ...eSAT Journals
Abstract In this work, automatic detection and diagnosis of gear condition monitoring technique is presented. The vibration signals in time domain wereobtained from a fault simulator apparatus from a healthy gear and an induced faulty gear. These time domain signals were processed using Laplace and Morlet wavelet based enveloped power spectrum to detect the faults in gears. The vibration signals obtained were filtered to enhance the signal components before the application of wavelet analysis. The time and frequency domain features extracted from Laplace wavelet based wavelet transform are used as input to ANN for gear fault classification. Genetic algorithm was used to optimize the wavelet and ANN classification parameters. The result shows the successful classification of ANN test process. Index Terms:Continuous wavelet transform, Envelope power spectrum, Wavelet, Filtering, ANN.
This paper introduces the Artifi cial Neural Networks (ANN) function to model probabilistic dependencies, in supervised classification tasks for discrimination between earthquakes and explosions problems. ANNs are regarded as the discriminating tools to classify the natural seismic events (earthquakes) from the artifi cial ones (Man-made explosions) based on the seismic signals recorded at regional distances. The bulk of our novel is to improve the obtained numerical results using this advance technique. The ANNs, by testing the different types of seismic features, showed the potential application of this method to discriminate the classes. During the above study, we found out that the Neural Networks have been used in a fully innovative manner in this work. Here the ARMA coefficients filters detects
the type of the source whenever a natural or artificial source changes the nature of the background noise of the seismograms. During the above study, we found out that this algorithm is sometimes capable to alarm the further natural seismological events just a little before the onset.
Multi-Target Classification Using Acoustic Signatures in Wireless Sensor Netw...CSCJournals
Classification of ground vehicles based on acoustic signals using wireless sensor networks is a crucial task in many applications such as battlefield surveillance, border monitoring, and traffic control. Different signal processing algorithms and techniques that are used in classification of ground moving vehicles in wireless sensor networks are surveyed in this paper. Feature extraction techniques and classifiers are discussed for single and multiple vehicles based on acoustic signals. This paper divides the corresponding literature into three main areas: feature extraction, classification techniques, and collaboration and information fusion techniques. The open research issues in these areas are also pointed out in this paper. This paper evaluates five different classifiers using two different feature extraction methods. The first one is based on the spectrum analysis and the other one is based on wavelet packet transform.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Correlation Analysis of Tool Wear and Cutting Sound SignalIJRES Journal
With the classic signal analysis and processing method, the cutting of the audio signal in time
domain and frequency domain analysis. We reached the following conclusions: in the time domain analysis,
cutting audio signals mean and the variance associated with tool wear state change occurred did not change
significantly, and tool wear is not high degree of correlation, and the mean-square value of the audio signal
changes in the size and tool wear the state has a good relationship.
Generation of Quantum Photon Information Using Extremely Narrow Optical Tweez...University of Malaya (UM)
A system of microring resonator (MRR) is presented to generate extremely narrow optical tweezers. An add/drop filter system consisting of one centered ring and one smaller ring on the left side can be used to generate extremely narrow pulse of optical tweezers. Optical tweezers generated by the dark-Gaussian behavior propagate via the MRRs system, where the input Gaussian pulse controls the output signal at the drop port of the system. Here the output optical tweezers can be connected to a quantum signal processing system (receiver), where it can be used to generate high capacity quantum codes within series of MRR’s and an add/drop filter. Detection of the encoded signals known as quantum bits can be done by the receiver unit system. Generated entangled photon pair propagates via an optical communication link. Here, the result of optical tweezers with full width at half maximum (FWHM) of 0.3 nm, 0.8 nm and 1.6 nm, 1.3 nm are obtained at the through and drop ports of the system respectively. These results used to be transmitted through a quantum signal processor via an optical computer network communication link.
An Adaptive Two-level Filtering Technique for Noise Lines in Video ImagesCSCJournals
Due to narrow-band noise signals in transmission channels, visible lines of disturbance can appear in video images. In this paper, an adaptive method based on two-level filtering is proposed to enhance the visual quality of such images. In the first level, an adaptive orientation selective filter detects and clears the noisy lines in the image. In the second level, a median filter repairs defects resulting from the orientation selective filtering process and also filters the wide-band impulsive noise. It was observed that in case of periodic noisy lines in TV images, this filtering technique can sufficiently enhance the image quality and improve the SNR level.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Frequency based criterion for distinguishing tonal and noisy spectral componentsCSCJournals
A frequency-based criterion for distinguishing tonal and noisy spectral components is proposed. For considered spectral local maximum two instantaneous frequency estimates are determined and the difference between them is used in order to verify whether component is noisy or tonal. Since one of the estimators was invented specially for this application its properties are deeply examined. The proposed criterion is applied to the stationary and nonstationary sinusoids in order to examine its efficiency.
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.
Similar to IRJET- A Review of Music Analysis Techniques (20)
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.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
About
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.
• 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.
Technical Specifications
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.
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.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.