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Back-Propagation (BP) Neural Network

Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

... Recurrent neural network (RNN) has been widely used as a tool in the data ...This network can be educated with gradient descent back ...recurrent network (ERN) and back ...

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Implementation of Neural Network Back Propagation Training Algorithm on FPGA

Implementation of Neural Network Back Propagation Training Algorithm on FPGA

... Artificial Neural Network (ANN) chip, which can be trained to implement certain ...of neural networks is done off-line using software tools in the computer ...The neural networks trained ...

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Diagnosis of thyroid disorders using Back propagation method

Diagnosis of thyroid disorders using Back propagation method

... decisions propagation algorithm is significant. Neural networks have recently attracted more attention due to their ability to learn complex and non-linear ...Artificial neural networks can be viewed ...

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Classification Using Two Layer Neural Network Back Propagation Algorithm

Classification Using Two Layer Neural Network Back Propagation Algorithm

... layer neural network back propagation method was proposed to diagnose the breast ...layer neural network back propagation algorithm input layer is not counted ...

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An Efficient and Robust Fall Detection System Using Wireless Gait Analysis Sensor with Artificial Neural Network (ANN) and Support Vector Machine (SVM) Algorithms

An Efficient and Robust Fall Detection System Using Wireless Gait Analysis Sensor with Artificial Neural Network (ANN) and Support Vector Machine (SVM) Algorithms

... used Back Propagation Artificial Neural Network (BP-ANN) and Support Vector Machine (SVM) based on the 6 features extracted from the raw ...(at back) or as a belt-clip in front ...

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Performance comparison of three artificial neural network methods for classification of electroencephalograph signals of five mental tasks

Performance comparison of three artificial neural network methods for classification of electroencephalograph signals of five mental tasks

... of neural network with resilient back propagation training method, support vector machine and radial bases function Neural Net- work for classifying of mental tasks ...Function) ...

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A New Approach for Rainfall Prediction using  Artificial Neural Network

A New Approach for Rainfall Prediction using Artificial Neural Network

... Abstract: Rainfall is considered as one of the major components of the weather forecasting. In the current world climate change, the accuracy of rainfall forecasting model is very important factor. Rainfall affects the ...

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Intelligent Search for Distributed Information Sources Using Heterogeneous Neural Networks

Intelligent Search for Distributed Information Sources Using Heterogeneous Neural Networks

... neous neural networks can be used in the design of an intelligent distributed in- formation retrieval (DIR) ...typical neural network models - Kohoren’s SOFM Network, Hopfield Network, ...

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Exudates Detection with DBSCAN clustering and Back Propagation Neural Network

Exudates Detection with DBSCAN clustering and Back Propagation Neural Network

... outward toward centre of the retina. These features are used to train the Gaussian Support Vector Machine to label individual patches of image. Vijayakumari and SuriyaNaraynan [9] used template matching for optic disc ...

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A review on Compressing Image Using Neural Network techniques

A review on Compressing Image Using Neural Network techniques

... the back propagation neural network and also combining the Levenberg-Marquardt concept with ...the network based upon the complexness of the value of ...the back ...

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Resilient Back Propagation Algorithm in the Prediction of Mother to Child Transmission of HIV

Resilient Back Propagation Algorithm in the Prediction of Mother to Child Transmission of HIV

... yet neural network techniques are major participants for prediction ...resilient back propagation algo- rithm is used for training the Neural Network and Multilayer Feed forward ...

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New Approaches for Image Compression Using Neural Network

New Approaches for Image Compression Using Neural Network

... type neural network which is used to change the dimension of feature eigenvector matrix effi- ciently as well as reconstruction of an original image ...forward back propagation neural ...

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A Robust Intrusion Detection System by Utilizing Support Vector Machine and Error Back Propagation Neural Network

A Robust Intrusion Detection System by Utilizing Support Vector Machine and Error Back Propagation Neural Network

... Abstract: The concept of Intrusion Detection System is used in the work. The data set is used for training and testing. Various numeric features of dataset are selected for better accuracy.SVM that is Support Vector ...

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STUDIES ON IMPROVING TEXTURE SEGMENTATION PERFORMANCE USING GENERALIZED GAUSSIAN 
MIXTURE MODEL INTEGRATING DCT AND LBP

STUDIES ON IMPROVING TEXTURE SEGMENTATION PERFORMANCE USING GENERALIZED GAUSSIAN MIXTURE MODEL INTEGRATING DCT AND LBP

... years, Neural Networks (NN) have been in ...the network frameworks, in two separate cases: The first is the typically utilized approximation error for the present data, and the second is the capacity of the ...

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Face Detection and Recognition using Back Propagation Neural Network (BPNN)

Face Detection and Recognition using Back Propagation Neural Network (BPNN)

... Feed-Forward network consists of a series of ...feed-forward network include fitting (fitnet) and pattern recognition (patternnet) ...backpropagation network is simply the application of ...

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License Plate Recognition System using Back Propagation Neural Network

License Plate Recognition System using Back Propagation Neural Network

... 4: Back Propagation Neural Network extended gradient descent based Delta learning rule, commonly known as Back Propagation ...a neural network to perform some task, ...

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A new back propagation neural network optimized with cuckoo search algorithm

A new back propagation neural network optimized with cuckoo search algorithm

... Table 2 give an idea about the CPU time, number of epochs and the mean square error for the 2 bit XOR data sets with ten hidden neurons. From the table, we can identify that the proposed CSBP method has better result ...

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Medical Image Security Using Watermarking In Back Propagation Neural Network

Medical Image Security Using Watermarking In Back Propagation Neural Network

... a back propagation neural network where the secret image is embedded along with different noise ...existing neural network algorithms back propagation algorithm ...

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An Approach to Handwriting Recognition using Back Propagation Neural Network

An Approach to Handwriting Recognition using Back Propagation Neural Network

... the Back-Propagation Network, characters drawn with the help of a stylus can thus be ...shown back-propagation approach are acceptable for recognizing ...the neural ...

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Research of Teacher’s Performance Evaluation Model Based on AHP and Improved PSO BP Neural Network

Research of Teacher’s Performance Evaluation Model Based on AHP and Improved PSO BP Neural Network

... and BP network ...in BP neural ...of BP network. The total error formula of BP is the fitness function of particles, and the fitness value of particles is the total error, ...

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