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
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.
Analysis of Microstrip Finger on Bandwidth of Interdigital Band Pass Filter u...IJREST
ABSTRACT
In this paper, a novel method of bandwidth estimation using variation of finger length on interdigital band pass filter has been presented using artificial neural networks for desired frequency range between 1.5--3.5GHz. Interdigital filter is multifinger periodic structure which offers compact filter design space. An ANN model has been developed and tested for estimating the cut off frequency of band pass filter and performance is evaluated in terms of mean square error and concluded that RBF network is more accurate than MLPFFBP. The proposed method of design provides the exact bandwidth for particular finger length of filter without using painstaking calculation.
Keyword - Artificial neural networks (ANN), Multi layer Perceptron feed Forward back propagation (MLPFFBP), Interdigital
Optimized sensor nodes by fault node recovery algorithmeSAT Journals
Abstract This paper proposes fault node recovery algorithm to enhance the lifetime of wireless sensor networks when some of the sensor nodes shut down due to absence of battery power. The proposed algorithm combined Grade diffusion algorithm with genetic algorithm. The algorithm can result replacement of fewer sensor nodes and more reused routing paths. The proposed algorithm increases the number of active nodes, reduces dataloss during transmission, and reduces energy consumption. Keywords: Wireless Sensor Networks, Energy Consumption, Fault Node Recovery.
Fuzzy Type Image Fusion Using SPIHT Image Compression TechniqueIJERA Editor
This paper presents a fuzzy type image fusion technique using Set Partitioning in Hierarchical Trees (SPIHT).
It is concluded that fusion with higher single levels provides better fusion quality. This technique can be used
for fusion of fuzzy images as well as multi model image fusion. The proposed algorithm is very simple, easy to
implement and could be used for real time applications. This is paper also provided comparatively studied
between proposed and previous existing technique and validation of the proposed algorithm as Peak Signal to
Noise Ratio (PSNR), Root Mean Square Error (RMSE).
Optimization of workload prediction based on map reduce frame work in a cloud...eSAT Journals
Abstract Nowadays cloud computing is emerging Technology. It is used to access anytime and anywhere through the internet. Hadoop is an open-source Cloud computing environment that implements the Googletm MapReduce framework. Hadoop is a framework for distributed processing of large datasets across large clusters of computers. This paper proposes the workload of jobs in clusters mode using Hadoop. MapReduce is a programming model in hadoop used for maintaining the workload of the jobs. Depend on the job analysis statistics the future workload of the cluster is predicted for potential performance optimization by using genetic algorithm. Key Words: Cloud computing, Hadoop Framework, MapReduce Analysis, Workload
Design of c slotted microstrip antenna using artificial neural network modeleSAT Journals
Abstract In this paper, neural network model has been used to estimation of resonance frequency of a coaxial feed C-slotted Microstrip Antenna. The Multi-Layer Perceptron Feed forward back Propagation (MLPFFBP) and Radial basis function Artificial Neural Network (RBFANN) have been used to implement the neural network model. A relative performance analysis of the proposed neural network for different training algorithms. Number of neurons and number of hidden layer is also carried out for estimating the resonance frequency. The method of moment (MOM) based IE3D software was used to generate data dictionary for training and validation set of ANN. The results obtain using ANN are compared with simulation feeding and found quite satisfactory and also it is concluded that RBFANN network is more accurate and fast compared to MLPFFBP network algorithm. Index Terms: Artificial Neural Network, C slot, Microstrip Antenna, Multilayer Feed Forward Networks, Radial basis function Artificial Neural Network, Resonance frequency.
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.
Analysis of Microstrip Finger on Bandwidth of Interdigital Band Pass Filter u...IJREST
ABSTRACT
In this paper, a novel method of bandwidth estimation using variation of finger length on interdigital band pass filter has been presented using artificial neural networks for desired frequency range between 1.5--3.5GHz. Interdigital filter is multifinger periodic structure which offers compact filter design space. An ANN model has been developed and tested for estimating the cut off frequency of band pass filter and performance is evaluated in terms of mean square error and concluded that RBF network is more accurate than MLPFFBP. The proposed method of design provides the exact bandwidth for particular finger length of filter without using painstaking calculation.
Keyword - Artificial neural networks (ANN), Multi layer Perceptron feed Forward back propagation (MLPFFBP), Interdigital
Optimized sensor nodes by fault node recovery algorithmeSAT Journals
Abstract This paper proposes fault node recovery algorithm to enhance the lifetime of wireless sensor networks when some of the sensor nodes shut down due to absence of battery power. The proposed algorithm combined Grade diffusion algorithm with genetic algorithm. The algorithm can result replacement of fewer sensor nodes and more reused routing paths. The proposed algorithm increases the number of active nodes, reduces dataloss during transmission, and reduces energy consumption. Keywords: Wireless Sensor Networks, Energy Consumption, Fault Node Recovery.
Fuzzy Type Image Fusion Using SPIHT Image Compression TechniqueIJERA Editor
This paper presents a fuzzy type image fusion technique using Set Partitioning in Hierarchical Trees (SPIHT).
It is concluded that fusion with higher single levels provides better fusion quality. This technique can be used
for fusion of fuzzy images as well as multi model image fusion. The proposed algorithm is very simple, easy to
implement and could be used for real time applications. This is paper also provided comparatively studied
between proposed and previous existing technique and validation of the proposed algorithm as Peak Signal to
Noise Ratio (PSNR), Root Mean Square Error (RMSE).
Optimization of workload prediction based on map reduce frame work in a cloud...eSAT Journals
Abstract Nowadays cloud computing is emerging Technology. It is used to access anytime and anywhere through the internet. Hadoop is an open-source Cloud computing environment that implements the Googletm MapReduce framework. Hadoop is a framework for distributed processing of large datasets across large clusters of computers. This paper proposes the workload of jobs in clusters mode using Hadoop. MapReduce is a programming model in hadoop used for maintaining the workload of the jobs. Depend on the job analysis statistics the future workload of the cluster is predicted for potential performance optimization by using genetic algorithm. Key Words: Cloud computing, Hadoop Framework, MapReduce Analysis, Workload
Design of c slotted microstrip antenna using artificial neural network modeleSAT Journals
Abstract In this paper, neural network model has been used to estimation of resonance frequency of a coaxial feed C-slotted Microstrip Antenna. The Multi-Layer Perceptron Feed forward back Propagation (MLPFFBP) and Radial basis function Artificial Neural Network (RBFANN) have been used to implement the neural network model. A relative performance analysis of the proposed neural network for different training algorithms. Number of neurons and number of hidden layer is also carried out for estimating the resonance frequency. The method of moment (MOM) based IE3D software was used to generate data dictionary for training and validation set of ANN. The results obtain using ANN are compared with simulation feeding and found quite satisfactory and also it is concluded that RBFANN network is more accurate and fast compared to MLPFFBP network algorithm. Index Terms: Artificial Neural Network, C slot, Microstrip Antenna, Multilayer Feed Forward Networks, Radial basis function Artificial Neural Network, Resonance frequency.
An Artificial Intelligence Approach to Ultra High Frequency Path Loss Modelli...ijtsrd
This study proposes Artificial Intelligence AI based path loss prediction models for the suburban areas of Abuja, Nigeria. The AI based models were created on the bases of two deep learning networks, namely the Adaptive Neuro Fuzzy Inference System ANFIS and the Generalized Radial Basis Function Neural network RBF NN . These prediction models were created, trained, validated and tested for path loss prediction using path loss data recorded at 1800MHz from multiple Base Transceiver Stations BTSs distributed across the areas under investigation. Results indicate that the ANFIS and RBF NN based models with Root Mean Squared Error RMSE values of 5.30dB and 5.31dB respectively, offer greater prediction accuracy over the widely used empirical COST 231 Hata, which has an RMSE of 8.18dB. Deme C. Abraham ""An Artificial Intelligence Approach to Ultra-High Frequency Path Loss Modelling of the Suburban Areas of Abuja, Nigeria"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30227.pdf
Paper Url : https://www.ijtsrd.com/computer-science/artificial-intelligence/30227/an-artificial-intelligence-approach-to-ultra-high-frequency-path-loss-modelling-of-the-suburban-areas-of-abuja-nigeria/deme-c-abraham
Performance analysis of dwdm based fiber optic communication with different m...eSAT Journals
Abstract Dense Wavelength Division multiplexing (DWDM) is a novel technology that can improve the channel capacity and meet growing demands for bandwidth of the optical fiber communication system. This technology utilizes a composite optical signal carrying multiple information streams. Each information streams transmitted on a distinct optical wavelength onto a single fiber. The performance of DWDM is degraded by non-linear optical effects. They are Cross phase modulation (XPM), Self phase modulation (SPM), four wave mixing (FWM), stimulated brillouin scattering (SBS) and stimulated Raman scattering (SRS). In this paper we analyze the performance of Dense Wavelength Division Multiplexing (DWDM) based fiber optic communication system at different modulation schemes, various power level and different number of data channels. we use the dispersion compensation fiber along with single mode fiber (SMF) for length of 100km at 1550nm to reduce the dispersion of optical signal. The performance of improved detected signals has been evaluated by the analysis of Quality factor and bit error rate (BER). The simulation studies are carried out using optisystem software from optiwave. Keywords: DWDM, cross-phase modulation, self-phase modulation, four wave mixing, stimulated Raman scattering, dispersion compensation fiber, NRZ, RZ, EDFA.
Architecture neural network deep optimizing based on self organizing feature ...journalBEEI
Forward neural network (FNN) execution relying on the algorithm of training and architecture selection. Different parameters using for nip out the architecture of FNN such as the connections number among strata, neurons hidden number in each strata hidden and hidden strata number. Feature architectural combinations exponential could be uncontrollable manually so specific architecture can be design automatically by using special algorithm which build system with ability generalization better. Determination of architecture FNN can be done by using the algorithm of optimization numerous. In this paper methodology new proposes achievement where FNN neurons respective with hidden layers estimation work where in this work collect algorithm training self organizing feature map (SOFM) with advantages to explain how the best architectural selected automatically by SOFM from criteria error testing based on architecture populated. Different size of dataset benchmark of 4 classifications tested for approach proposed.
IMAGE AUTHENTICATION THROUGH ZTRANSFORM WITH LOW ENERGY AND BANDWIDTH (IAZT)IJNSA Journal
In this paper a Z-transform based image authentication technique termed as IAZT has been proposed to
authenticate gray scale images. The technique uses energy efficient and low bandwidth based invisible data
embedding with a minimal computational complexity. Near about half of the bandwidth is required
compared to the traditional Z–transform while transmitting the multimedia contents such as images with
authenticating message through network. This authenticating technique may be used for copyright
protection or ownership verification. Experimental results are computed and compared with the existing
authentication techniques like Li’s method [11], SCDFT [13], Region-Based method [14] and many more
based on Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Image Fidelity (IF), Universal
Quality Image (UQI) and Structural Similarity Index Measurement (SSIM) which shows better performance
in IAZT.
SAR Image Classification by Multilayer Back Propagation Neural NetworkIJMTST Journal
A novel descriptive feature extraction method of Discrete Fourier transform and neural network classifier for classification of Synthetic Aperture Radar (SAR) images is proposed. The classification process has the following stages (1) Image Segmentation using statistical Region Merging (SRM) (2) Polar transform and Feature extraction using Discrete Fourier Transform (3) Neural Network classification using back propagation. This is generally the first step in image analysis. Segmentation subdivides an image into its constituent parts or objects. The level to which this subdivision is carried depends on the problem being solved. The image segmentation in this study is performed using Statistical Region Merging proposed Richard Nock and Frank Nielsen. The key idea of the Statistical Region Merging model is to formulate image segmentation as an inference problem. Here the merging procedure is based on the theorem. Feature vectors as the input for the neural network. Polar transform is applied to segmented SAR image. The rotation problem under the Cartesian coordinates becomes the translation problem under the polar coordinates.
An energy-efficient cluster head selection in wireless sensor network using g...TELKOMNIKA JOURNAL
Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms.
Simulation of Single and Multilayer of Artificial Neural Network using Verilogijsrd.com
Artificial neural network play an important role in VLSI circuit to find and diagnosis multiple fault in digital circuit. In this paper, the example of single layer and multi-layer neural network had been discussed secondly implement those structure by using verilog code and same idea must be implement in mat lab for getting number of iteration and verilog code gives us time taken to adjust the weight when error become almost equal to zero. The purposed aim at reducing resource requirement, without much compromises on the speed that neural network can be realized on single chip at lower cost.
Macromodel of High Speed Interconnect using Vector Fitting Algorithmijsrd.com
At high frequency efficient macromodeling of high speed interconnects is all time challenging task. We have presented systematic methodologies to generate rational function approximations of high-speed interconnects using vector fitting technique for any type of termination conditions and construct efficient multiport model, which is easily and directly compatible with circuit simulators.
This paper presents a study of the efficiency and performance speedup achieved by applying Graphics Processing Units for Face Recognition Solutions. We explore one of the possibilities of parallelizing and optimizing a well-known Face Recognition algorithm, Principal Component Analysis (PCA) with Eigenfaces. In recent years, the Graphics Processing Units (GPU) has been the subject of extensive research and the computation speed of GPUs has been rapidly increasing.
Design of area and power efficient half adder using transmission gateeSAT Journals
Abstract This paper gives an idea to reduce power and surface area of half adder circuit using very popular technique i.e. transmission gate. An adder is a digital circuit that performs addition of two numbers. In many computers and other kind of processors, adders are used not only in arithmetic logic unit but also in other parts of the processors where they are used to calculate addresses, table indices and similar operations .in this paper two bit addition has been done using conventional and transmission gate level and power, area and number of transistors are the scope of comparison. According to the simulation result, power and area are reduced by 55.35 % and 40.269% respectively when the circuit is implemented by transmission gate .thus transmission gate has become a very popular and useful technique to implement digital circuits which help to reduce power, surface area as well as number of transistors. Keywords: Transmission gate (TG), Half adder, CMOS logic gates, Surface area, Power.
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
Online social network mining current trends and research issueseSAT 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
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 TechnologyIJRET : 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
A comprehensive review on performance of aodv protocol for wormhole attackeSAT 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
Biochemical and molecular characterization of antagonistic bacteria against y...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
An Artificial Intelligence Approach to Ultra High Frequency Path Loss Modelli...ijtsrd
This study proposes Artificial Intelligence AI based path loss prediction models for the suburban areas of Abuja, Nigeria. The AI based models were created on the bases of two deep learning networks, namely the Adaptive Neuro Fuzzy Inference System ANFIS and the Generalized Radial Basis Function Neural network RBF NN . These prediction models were created, trained, validated and tested for path loss prediction using path loss data recorded at 1800MHz from multiple Base Transceiver Stations BTSs distributed across the areas under investigation. Results indicate that the ANFIS and RBF NN based models with Root Mean Squared Error RMSE values of 5.30dB and 5.31dB respectively, offer greater prediction accuracy over the widely used empirical COST 231 Hata, which has an RMSE of 8.18dB. Deme C. Abraham ""An Artificial Intelligence Approach to Ultra-High Frequency Path Loss Modelling of the Suburban Areas of Abuja, Nigeria"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30227.pdf
Paper Url : https://www.ijtsrd.com/computer-science/artificial-intelligence/30227/an-artificial-intelligence-approach-to-ultra-high-frequency-path-loss-modelling-of-the-suburban-areas-of-abuja-nigeria/deme-c-abraham
Performance analysis of dwdm based fiber optic communication with different m...eSAT Journals
Abstract Dense Wavelength Division multiplexing (DWDM) is a novel technology that can improve the channel capacity and meet growing demands for bandwidth of the optical fiber communication system. This technology utilizes a composite optical signal carrying multiple information streams. Each information streams transmitted on a distinct optical wavelength onto a single fiber. The performance of DWDM is degraded by non-linear optical effects. They are Cross phase modulation (XPM), Self phase modulation (SPM), four wave mixing (FWM), stimulated brillouin scattering (SBS) and stimulated Raman scattering (SRS). In this paper we analyze the performance of Dense Wavelength Division Multiplexing (DWDM) based fiber optic communication system at different modulation schemes, various power level and different number of data channels. we use the dispersion compensation fiber along with single mode fiber (SMF) for length of 100km at 1550nm to reduce the dispersion of optical signal. The performance of improved detected signals has been evaluated by the analysis of Quality factor and bit error rate (BER). The simulation studies are carried out using optisystem software from optiwave. Keywords: DWDM, cross-phase modulation, self-phase modulation, four wave mixing, stimulated Raman scattering, dispersion compensation fiber, NRZ, RZ, EDFA.
Architecture neural network deep optimizing based on self organizing feature ...journalBEEI
Forward neural network (FNN) execution relying on the algorithm of training and architecture selection. Different parameters using for nip out the architecture of FNN such as the connections number among strata, neurons hidden number in each strata hidden and hidden strata number. Feature architectural combinations exponential could be uncontrollable manually so specific architecture can be design automatically by using special algorithm which build system with ability generalization better. Determination of architecture FNN can be done by using the algorithm of optimization numerous. In this paper methodology new proposes achievement where FNN neurons respective with hidden layers estimation work where in this work collect algorithm training self organizing feature map (SOFM) with advantages to explain how the best architectural selected automatically by SOFM from criteria error testing based on architecture populated. Different size of dataset benchmark of 4 classifications tested for approach proposed.
IMAGE AUTHENTICATION THROUGH ZTRANSFORM WITH LOW ENERGY AND BANDWIDTH (IAZT)IJNSA Journal
In this paper a Z-transform based image authentication technique termed as IAZT has been proposed to
authenticate gray scale images. The technique uses energy efficient and low bandwidth based invisible data
embedding with a minimal computational complexity. Near about half of the bandwidth is required
compared to the traditional Z–transform while transmitting the multimedia contents such as images with
authenticating message through network. This authenticating technique may be used for copyright
protection or ownership verification. Experimental results are computed and compared with the existing
authentication techniques like Li’s method [11], SCDFT [13], Region-Based method [14] and many more
based on Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Image Fidelity (IF), Universal
Quality Image (UQI) and Structural Similarity Index Measurement (SSIM) which shows better performance
in IAZT.
SAR Image Classification by Multilayer Back Propagation Neural NetworkIJMTST Journal
A novel descriptive feature extraction method of Discrete Fourier transform and neural network classifier for classification of Synthetic Aperture Radar (SAR) images is proposed. The classification process has the following stages (1) Image Segmentation using statistical Region Merging (SRM) (2) Polar transform and Feature extraction using Discrete Fourier Transform (3) Neural Network classification using back propagation. This is generally the first step in image analysis. Segmentation subdivides an image into its constituent parts or objects. The level to which this subdivision is carried depends on the problem being solved. The image segmentation in this study is performed using Statistical Region Merging proposed Richard Nock and Frank Nielsen. The key idea of the Statistical Region Merging model is to formulate image segmentation as an inference problem. Here the merging procedure is based on the theorem. Feature vectors as the input for the neural network. Polar transform is applied to segmented SAR image. The rotation problem under the Cartesian coordinates becomes the translation problem under the polar coordinates.
An energy-efficient cluster head selection in wireless sensor network using g...TELKOMNIKA JOURNAL
Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms.
Simulation of Single and Multilayer of Artificial Neural Network using Verilogijsrd.com
Artificial neural network play an important role in VLSI circuit to find and diagnosis multiple fault in digital circuit. In this paper, the example of single layer and multi-layer neural network had been discussed secondly implement those structure by using verilog code and same idea must be implement in mat lab for getting number of iteration and verilog code gives us time taken to adjust the weight when error become almost equal to zero. The purposed aim at reducing resource requirement, without much compromises on the speed that neural network can be realized on single chip at lower cost.
Macromodel of High Speed Interconnect using Vector Fitting Algorithmijsrd.com
At high frequency efficient macromodeling of high speed interconnects is all time challenging task. We have presented systematic methodologies to generate rational function approximations of high-speed interconnects using vector fitting technique for any type of termination conditions and construct efficient multiport model, which is easily and directly compatible with circuit simulators.
This paper presents a study of the efficiency and performance speedup achieved by applying Graphics Processing Units for Face Recognition Solutions. We explore one of the possibilities of parallelizing and optimizing a well-known Face Recognition algorithm, Principal Component Analysis (PCA) with Eigenfaces. In recent years, the Graphics Processing Units (GPU) has been the subject of extensive research and the computation speed of GPUs has been rapidly increasing.
Design of area and power efficient half adder using transmission gateeSAT Journals
Abstract This paper gives an idea to reduce power and surface area of half adder circuit using very popular technique i.e. transmission gate. An adder is a digital circuit that performs addition of two numbers. In many computers and other kind of processors, adders are used not only in arithmetic logic unit but also in other parts of the processors where they are used to calculate addresses, table indices and similar operations .in this paper two bit addition has been done using conventional and transmission gate level and power, area and number of transistors are the scope of comparison. According to the simulation result, power and area are reduced by 55.35 % and 40.269% respectively when the circuit is implemented by transmission gate .thus transmission gate has become a very popular and useful technique to implement digital circuits which help to reduce power, surface area as well as number of transistors. Keywords: Transmission gate (TG), Half adder, CMOS logic gates, Surface area, Power.
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
Online social network mining current trends and research issueseSAT 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
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 TechnologyIJRET : 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
A comprehensive review on performance of aodv protocol for wormhole attackeSAT 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
Biochemical and molecular characterization of antagonistic bacteria against y...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
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
Realization of high performance run time loadable mips soft-core processoreSAT 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
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
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.
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.
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
Exploring the preferred temperature on occupants thermal comfort in the humid...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
Comparative studies on flotation of kasolite using cationic and anionic surfa...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
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
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
Analysis of mhd non darcian boundary layer flow and heat transfer over an exp...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
Numerical simulation of friction stir butt welding processes for az91 magnesi...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
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
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
In this paper we are interested to calculate the resonant frequency of rectangular patch antenna using artificial neural networks based on the multilayered perceptrons. The artificial neural networks built, transforms the inputs which are, the width of the patch W, the length of the patch L, the thickness of the substrate h and the dielectric permittivity ε_r to the resonant frequency fr which is an important parameter to design a microstrip patch antenna.The proposed method based on artificial neural networks is compared to some analytical methods using some statistical criteria. The obtained results demonstrate that artificial neural networks are more adequate to achieve the purpose than the other methods and present a good argument with the experimental results available in the literature. Hence, the artificial neural networks can be used by researchers to predict the resonant frequency of a rectangular patch antenna knowing length (L), width (W), thickness (h) and dielectric permittivity 〖(ε〗_r) with a good accuracy.
Face recognition using gaussian mixture model & artificial neural networkeSAT Journals
Abstract
Face recognition is a non-contact and friendly biometric identification technology. It has broad application prospects in the
military, public security and economic security. In this work, we also consider illumination variable database. The images have
taken from far distance and do not consider the close view face of the individual as in most of the face databases, clear face view
has been considered. In this first we located face as region of interest and then LBP and LPQ descriptors are used which is
illuminance invariant in nature. After this GMM has been used to reduce feature set by taking negative log-likelihood from each
LBP and LPQ descripted image histograms. After this ANN consumes stayed used for organization purposes. The investigational
consequencesshow excellent correctness rates in overall testing of input data.
Keywords: Illumination invariant, face recognition, LBP, LPQs,GMM,ANN
An Ant colony optimization algorithm to solve the broken link problem in wire...IJERA Editor
Aco is a well –known metahuristic in which a colony of artificial ants cooperates in explain Good solution to a combinational optimization problem. Wireless sensor consisting of nodes with limited power is deployed to gather useful information From the field. In wireless sensor network it is critical to collect the information in an energy efficient Manner.ant colony optimization, a swarm intelligence based optimization technique, is widely used In network routing. A novel routing approach using an ant colony optimization algorithm is proposed for wireless sensor Network consisting of stable nodes illustrative example details description and cooperative performance test result the proposed approach are included. The approach is also implementing to a small sized hardware component as a router chip simulation result show that proposed algorithm Provides promising solution allowing node designers to efficiency operate routing tasks.
Reflectivity Parameter Extraction from RADAR Images Using Back Propagation Al...IJECEIAES
Pattern recognition has been acknowledged as one of the promising research areas and it has drawn the awareness among many researchers since its existence at the beginning of the nineties. Multilayer Neural networks are used in pattern Recognition and classification based on the features derived from the input patterns. The Reflectivity information extracted from the Doppler Weather Radar (DWR) image helps in identifying the convective cloud type which has a strong relation to the precipitation rate. The reflectivity information is rooted in the DWR image with the help of colors and color bar is provided to distinguish among different reflectivity information. Artificial Neural network predicts the color based on the maximum likelihood estimation problem. This paper presents a best possible backpropagation algorithm for color identification in DWR images by comparing various backpropagation algorithms such as LevenbergMarquardt, Conjugate gradient, and Resilient back propagation etc.,. Pattern recognition using Neural networks presents better results compared to standard distance measures. It is observed that Levenberg-Marquardt backpropagation algorithm yields a regression value of 99% approximately and accuracy of 98%.
Artificial Neural Networks (ANNS) For Prediction of California Bearing Ratio ...IJMER
The behaviour of soil at the location of the project and interactions of the earth materials during and after construction has a major influence on the success, economy and safety of the work. Another complexity associated with some geotechnical engineering materials, such as sand and gravel, is the difficulty in obtaining undisturbed samples and time consuming involving skilled
technician. Knowledge of California Bearing Ratio (C.B.R) is essential in finding the road thickness. To cope up with the difficulties involved, an attempt has been made to model C.B.R in terms of Fine Fraction, Liquid Limit, Plasticity Index, Maximum Dry density, and Optimum Moisture content. A multi-layer perceptron network with feed forward back propagation is used to model varying the
number of hidden layers. For this purposes 50 soils test data was collected from the laboratory test
results. Among the test data 30 soils data is used for training and remaining 20 soils for testing using
60-40 distribution. The architectures developed are 5-4-1, 5-5-1, and 5-6-1. Model with 5-6-1 architecture is found to be quite satisfactory in predicting C.B.R of soils. A graph is plotted between
the predicted values and observed values of outputs for training and testing process, from the graph it
is found that all the points are close to equality line, indicating predicted values are close to observed
values
Artificial Neural Network in the Design of Rectangular Microstrip Antennaaciijournal
A simple design to compute accurate resonant frequencies and the electric fields of rectangular microstrip
antennas using artificial neural networks (ANN) is proposed. The ANN is developed to calculate the
frequency and antenna's field. ANN is designed using multilayer perceptron networks (MLP). The results
that were obtained accord the trained and tested data of ANN models. As a result, the ANN model is
presented as a substitutional method to the detailed electromagnetic design of rectangular microstrip
antenna.
Survey paper on adaptive beamforming lms,nlms and rls algorithms for smart an...eSAT Journals
Abstract
Smart antenna system is used to maximize the output power of signal in desired direction and minimize the power in unwanted direction. Smart antenna system consists of multiple numbers of elements. Basic concept in smart antenna technology is beam forming, it is mainly used to improve signal to noise ratio. Beam forming signal processing technique used in sensor arrays for directional signal transmission and reception. And it possible by combining the elements in phased array in such a way that signals at particular angles experiences constructive interference and others are destructive interferences. In smart antenna system we are using various algorithms to calculate the weights of smart antenna arrays to increase the output in desired direction and reduce the power in unwanted direction We are using different types of arrays i.e. linear array, circular array, planar array . Different algorithms are used to adjust the weights of the smart antenna system Basically Weights are nothing but Amplitude and phase of the signal. Adaptive algorithms update the weights of the array elements. LMS algorithm provides less convergence speed, and that is depends on the step size. LMS algorithm is widely used in adaptive filter due to its relative low computational complexity, good stability and relatively good robustness against the implementation errors. To improve the convergence rate NLMS algorithm is used. LMS algorithm having constant step size but in NLMS algorithm step size is depends on data at each iteration. Whereas RLS algorithm having minimum bit error rate but it required more computations than the LSM algorithm.
Keywords: Beamforming, smart antenna, complex weight, array geometry, Array factor
Prediction of Extreme Wind Speed Using Artificial Neural Network ApproachScientific Review SR
Prediction of an accurate wind speed of wind farms is necessary because of the intermittent nature
of wind for any region. Number of methods such as persistence, physical, statistical, spatial correlation, artificial
intelligence network and hybrid are generally available for prediction of wind speed. In this paper, ANN based
methods viz., Multi Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks are used. The
performance of the networks applied for prediction of wind speed is evaluated by model performance indicators
viz., Correlation Coefficient (CC), Model Efficiency (MEF) and Mean Absolute Percentage Error (MAPE).
Meteorological parameters such as maximum and minimum temperature, air pressure, solar radiation and
altitude are considered as input units for MLP and RBF networks to predict the extreme wind speed at Delhi.
The study shows the values of CC, MEF and MAPE between the observed and predicted wind speed (using
MLP) are computed as 0.992, 95.4% and 4.3% respectively while training the network data. For RBF network,
the values of CC, MEF and MAPE are computed as 0.992, 95.9% and 3.0% respectively. The model
performance analysis indicates the RBF is better suited network among two different networks studied for
prediction of extreme wind speed at Delhi.
Network Lifetime Enhancement by Node Deployment in WSNIJTET Journal
Abstract— The key challenge in wireless sensor network is network lifetime so it is necessary to increase the network lifetime. The work deals with the enhancement of the network lifetime for target coverage problem in wireless sensor network while deploying the sensor nodes. Initially sensor nodes and targets are placed randomly, where the targets are the not sensor nodes its external parameter. Network lifetime for this scenario is computed, where the sensing range and initial energy of the battery are assumed. Network lifetime is based on sensor nodes that monitor the targets and lifetime of battery. The randomly placed sensor nodes are redeployed using optimization algorithm called Artificial Bee Colony (ABC). The network lifetime for redeployed sensor nodes are computed and compared with randomly deployed sensor nodes.
Available transfer capability computations in the indian southern e.h.v power...eSAT Journals
Abstract This paper presents three methods for computing the available transfer capability (ATC). One method is the conventional method known as continuation repeated power flow (CRPF) and other two are the intelligent techniques known as radial basis function neural network (RBFNN), basic adaptive neuro fuzzy inference system (ANFIS). In these two intelligent techniques, the basic ANFIS works with a multiple input single output (MISO) and it is modified as multiple input multiple output (MIMO) ANFIS using the proposed MIMO ANFIS. The main intension of this proposed method is to utilise the significant features of ANFIS with respect to the multiple outputs, as the basic ANFIS has been proved as the best intelligent techniques in the modelling of any application, but it has a disadvantage of single output and this drawback will be overcome using the proposed MIMO ANFIS. In this paper, the latest Indian southern region extra high voltage (SREHV) 72-bus system considered as test system to obtain the ATC computations using three methods. The ATC computations at desired buses are obtained with and without contingencies and compared the conventional ATC computations with the intelligent techniques. The obtained results are scrupulously verified with different test patterns and observed that the accuracy of proposed method is proved as the best as compared to the other methods for computing ATC. In this way, this paper shows a better way to compute ATC for the different open power market system Keywords— Available Transfer Capability, Total Transfer Capability, Open Power Markets, Repeated Power Flow, Radial Basis Function Neural Networks, Adaptive Neuro Fuzzy Inference System etc.
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.
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Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
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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.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
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R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
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It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
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1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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DESIGN OF C-SLOTTED MICROSTRIP ANTENNA USING
ARTIFICIAL NEURAL NETWORK MODEL
Pritam Singha Roy1
, Samik Chakraborty2
1
Assistant Professor, Electronics Engineering, DIET, West Bengal, India
e-mail:prittam.pritam@gmail.com
2
Professor, Communication Engineering, Indian Maritime University, West Bengal, India
e-mail:chakra_samik@yahoo.com
Abstract
In this paper, neural network model has been used to estimation of resonance frequency of a coaxial feed C-slotted Microstrip
Antenna. The Multi-Layer Perceptron Feed forward back Propagation (MLPFFBP) and Radial basis function Artificial Neural
Network (RBFANN) have been used to implement the neural network model. A relative performance analysis of the proposed
neural network for different training algorithms. Number of neurons and number of hidden layer is also carried out for estimating
the resonance frequency. The method of moment (MOM) based IE3D software was used to generate data dictionary for training
and validation set of ANN. The results obtain using ANN are compared with simulation feeding and found quite satisfactory and
also it is concluded that RBFANN network is more accurate and fast compared to MLPFFBP network algorithm.
Index Terms: Artificial Neural Network, C slot, Microstrip Antenna, Multilayer Feed Forward Networks, Radial basis
function Artificial Neural Network, Resonance frequency.
------------------------------------------------------------------------------------------------------------------------------------------
1. INTRODUCTION
Microstrip antennas due to their many attractive features
have drawn attention of industries for an ultimate solution for
wireless communication. The existing era of wireless
communication has led to the design of an efficient, wide
band, low cost and small volume antennas which can readily
be incorporated into a broad spectrum of systems [1,
2].sufficient amount of work [3-10] indicates how ANN have
been used efficiently to design rectangular Microstrip
antenna for the determination of different patch dimensions
i,e length,width,resonant frequency, radiation efficiency etc.
In this paper, an attempt has been made to exploit the
capability of artificial neural networks to calculate the
resonating frequency of coaxial feed C-slotted Microstrip
patch antenna. The trained ANN is used to determine
different important antenna characteristics for various
structural input variables.Neoro models are computationally
much more efficient than EM models once they are trained
with reliable learning data obtained from a “fine” model by
either EM simulation or measurement [3, 4, 5, 6].The neuro
models can be used for efficient and accurate optimization
and design within the range of training.
In this work, the authors extend the work on the use of the
artificial neural network (ANN) technique taking into
account different variants of back propagation training
algorithm with MLPFFBP and RBF ANN model are stressed
upon in place of conventional numerical techniques for the
C-slot microstrip antenna design. Then, with the ANN
results, simulated results from the IE3D software are
compared.
2. DESIGN AND DATA GENERATION
Designing of micro strip patch antenna depends on three
parameters. In this paper The rectangular patch Microstrip
antenna is designed to resonate at 6.8 GHz frequency with
dielectric constant 2.2,Substrate thickness h = 1.5mm
,L=16.01mm and W=19.73mm. The width (W) and length
(L) of antenna are calculated from conventional equations
[11].
For generating data, we simulated the frequency domain
response of the antenna for various patch dimensions, using
method of moments based simulation software IE3DTM
.For
training and testing of the ANN, 100 data sets are generated
2. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 121
by simulation using IE3DTM
simulation software. Four
Antenna dimension as L1 is the horizontal slot length, W1 is
Figure.1 .C-slotted Microstrip Patch antenna
the vertical slot length,W2 and W3 are the upper and lower
vertical patch length respectively. Figure1. shows the layout
of a coaxial probe-fed C-slotted patch antenna.
The four dimensions L1,W1,W2 and W3 are varied from 0.1
to 3 mm and we have taken corresponding simulated
resonance frequencies. The feed position is varied in very
close steps varying around one sixth of the length (from
microstrip centre) within 1.5mm along the length. These
sampled points are then scaled to remain within the range
[-1, 1] and used as the training data for the network.
3. NETWORK ARCHITECHTURE AND
TRAINING
For the present work the Multi-Layer Perceptron Feed
forward back Propagation neural network [12, 13] and
Radial basis function Artificial Neural Network models are
used. These networks can be used as a general function
approximator.It can be approximate any function with a
finite number of discontinuous, arbitrary well given
sufficient neurons in the hidden layer. The model is trained
with 100 sets of input/output data, which are obtained by
IE3D software based on MoM. The model is trained for
different values of parameters (L1,W1,W2 and W3 )to get a
desired frequency.
3.1 Multi-Layer Perceptron Feed forward Back Propagation
(MLPFFBP) Neural Network.
MLP networks are feed forward networks trained with the
standard back propagation algorithms to achieve the
required degree of accuracy.
They are supervised networks, and also they required a
desired response to be trained. With one or two hidden
layers they can approximate virtually any input output map.
Figure 2. Three layer MLPFFBP network architecture
The weights of the networks are computed by training the
network using back propagation algorithm [14, 15].In
present work, the MLPFFBP (Levenberg-Marquardt)
architecture shown in Figure 2.
In this network there are four input neurons in the input
layer, 25 hidden neurons in the hidden layer and one output
neuron in the output layer. The training time is 26 seconds
and training performs in 250 epochs. In order to evaluate the
performance of proposed MLPFFBP-ANN based model for
the design of microstrip antenna, simulation results are
obtained using IE3D simulator and generated 82 input –
output training patterns and 18 inputs-outputs test patterns to
validate the model. During the training process the neural
network automatically adjusts its weights and threshold
values such that the error between predicted and sampled
outputs is minimized. The adjustments are computed by the
back propagation algorithm. The training algorithm most
suitable is trainlm.The error goal is 0.001.The transfer
function is tansig in the architecture.
Figure 3. Number of epochs to achieve minimum mean
square error level in case of MLPFFBP training algorithm
3. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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In Table I resonant frequencies obtained using IE3D
software and using MLPFFBP algorithm for different test
patterns are compared and Mean square error has been
calculated in Table I.
Table I: Comparison of results obtained using IE3D software
and MLPFFBP –ANN algorithm
Figure 3.shows the training performance of the developed
neural model for proposed antenna using MLPFFBP
algorithm. Model is trained in 250 epochs and the training
time was 26 seconds.
3.2 Radial basis function Artificial Neural Network
Radial basis function network [16, 17] is a feed forward
neural network with a single hidden layer that use radial
basis activation functions for hidden neurons.RBF networks
are applied for various microwave modeling purpose. The
RBF neural network has both a supervised and unsupervised
component to its learning. It consists of three layers of
neurons-input, hidden and output. The hidden layer neuron
represents a series of centers in the data space. Each of these
centers has an activation function, typically Gaussian. The
activation depends on the distance between the presented
input vector and the centre. The farther the vector is from
the centre, the lower is the activation and vice versa
[12].The generation of the centre and their widths is done
using an unsupervised k-means clustering algorithm. The
centre and widths created by this algorithm then form the
weights and biases of the hidden layer, which remain
unchanged once the clustering has been done.
The typical RBF network structure is given in Figure 4
Figure 4: RBF-NN Basic Structure
The parameters ci and εi are centre and standard deviations
of radial basis activation functions. Commonly used radial
basis activation functions are Gaussian and Multidquadratic.
Given the input x, the total input to the ith hidden neuron γi
is given by –
Where N is the number of hidden neurons. The output value
of the ith hidden neuron is Zi = σ (γi) ,where σ (γi) is a
radial basis function. Finally, the output of the RBF network
are computed from hidden neuron is given by-
Where wi is the weight of the link between the ith neuron of
the hidden layer and kth neuron of the output layer.
In RBF network, the spread value was chosen as 0.01,
which gives the best accuracy. The network was trained
with 82 samples and tested with 18 samples. In the structure
there is one input and one output was used for the analysis
ANN.
Figure 5. Number of epochs to achieve minimum mean
square error level in case of RBF network.
4. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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The RBF network automatically adjusts the number of
processing elements in the hidden layer till the defined
accuracy is reached. The training algorithm is unsupervised
k-means clustering algorithm.
Figure 5. shows the training performance of the developed
neural model using RBF Network. Model is trained 93
epochs.
It is clear that RBF network is much faster than feed forward
networks since RBF network is trained fewer epochs than
feed forward network
4. RESULTS AND DISCUSSION
The antenna fabricated for validation of ANN are simulated
using IE3D simulation software for comparison and
validation purpose of ANN, because the specification of
these antennas are not included in the training data base. The
results of IE3D simulation software and MLPFFBP
(Levenberg-Marquardt) training algorithm is shown in
Figure 6.
It has been established from Figure 3.that the MLPFFBP
training algorithm is the optimal model to achieve desirable
values of speed of convergence. It has been observed that
250 epochs are needed to reduce MSE level to a low value
1.01575e-005 for three layers MLPFFBP with transig as a
transfer function. Achievement of such a low value of
performance goal (MSE) and accuracy of 99.89% indicates
that ANN model is an accurate model for designing the
Microstrip patch antenna. It is observed that tansig is most
suitable transfer function for present work. Minimum MSE
is calculated after training the network and indicated in
Table I
As the work signifies RBF-ANN is also used to model the
Microstrip patch antenna. A Radial Basis Function neural
network has an input layer, a hidden layer and an output
layer. The neurons in the hidden layer contain Gaussian
transfer function whose outputs are inversely proportional to
the distance from the centre of the neuron. It is established
from Figure 5. That RBF is giving results not only more
accurate but fast also, the presented RBF network has
performed training in less epochs than MLPFFBP.So it is
concluded that RBF architecture is better from MLPFFBP to
the accuracy of 99.97% and quite faster comparatively.
CONCLUSIONS
Artificial neural network structure is used for analysis of
C-slotted Microstrip patch antenna characteristics.
Multilayer Perceptron trained in the backpropagation mode
(using Levenberg-Marquardt algorithm) and Radial basis
Function Network model are developed. The important
characteristics namely, resonance frequencies obtained with
the present techniques are closer to the experimental results
generated by simulating a large no. of C-slotted microstrip
patch antenna using IE3Dsoftware.The comprehensive
comparison found that RBF network is better than
MLPFFBP network in prediction accuracy, training time
and training speed. It proved that the RBF neural network is
more efficient and accurate than MLPFFBP neural network.
The developed neural network methodology can be
extended for characterizing other different shapes of
Microstrip antenna.
Figure 6. Comparison of frequency of antenna obtained using
IE3D simulation software and Trained with MLPFFBP.
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BIOGRAPHIES
Mr. Pritam Singha Roy ,Assistant
Professor in DIET and got M.Tech
degree in Electronics and Control
Engineering,Calcutta University,India,
in 2009. His current areas of interest
are design and development of
microstrip ,dielectric and metallic
antennas.
Dr. samik Chakraborty ,Professor at
Indian Maritime University,India..He
received Ph.D(Science) in 2009 ,from
Jadavpur University,Kolkata ,India.He
is currently supervising two doctoral
thesis.He has worked in different
research projects for National Defence
and Space Research Organizations