Description:This book presents a systematic approach to parallel implementation of feedforward neural networks on an array of transputers. The emphasis is on backpropagation learning and training set parallelism. Using systematic analysis, a theoretical model has been developed for the parallel implementation. The model is used to find the optimal mapping to minimize the training time for large backpropagation neural networks. The model has been validated experimentally on several well known benchmark problems. Use of genetic algorithms for optimizing the performance of the parallel implementations is described. Guidelines for efficient parallel implementations are highlighted.Contents: IntroductionTransputer Topologies for Parallel ImplementationDevelopment of a Theoretical Model for Training Set Parallelism in a Homogeneous Array of TransputersEqual Distribution of Patterns Amongst a Homogeneous Array of TransputersOptimization Model for Unequal Distribution of Patterns in a Homogeneous Array of TransputersPattern Allocation Schemes Using Genetic AlgorithmBibliographyIndexReadership: Graduate students, research scientists and practising engineers in artificial neural networks and parallel computing.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Parallel Implementations of Backpropagation Neural Networks on Transputers: A Study of Training Set Parallelism. To get started finding Parallel Implementations of Backpropagation Neural Networks on Transputers: A Study of Training Set Parallelism, you are right to find our website which has a comprehensive collection of manuals listed. Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
222
Format
PDF, EPUB & Kindle Edition
Publisher
World Scientific Publishing Company
Release
2014
ISBN
1299662498
Parallel Implementations of Backpropagation Neural Networks on Transputers: A Study of Training Set Parallelism
Description: This book presents a systematic approach to parallel implementation of feedforward neural networks on an array of transputers. The emphasis is on backpropagation learning and training set parallelism. Using systematic analysis, a theoretical model has been developed for the parallel implementation. The model is used to find the optimal mapping to minimize the training time for large backpropagation neural networks. The model has been validated experimentally on several well known benchmark problems. Use of genetic algorithms for optimizing the performance of the parallel implementations is described. Guidelines for efficient parallel implementations are highlighted.Contents: IntroductionTransputer Topologies for Parallel ImplementationDevelopment of a Theoretical Model for Training Set Parallelism in a Homogeneous Array of TransputersEqual Distribution of Patterns Amongst a Homogeneous Array of TransputersOptimization Model for Unequal Distribution of Patterns in a Homogeneous Array of TransputersPattern Allocation Schemes Using Genetic AlgorithmBibliographyIndexReadership: Graduate students, research scientists and practising engineers in artificial neural networks and parallel computing.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Parallel Implementations of Backpropagation Neural Networks on Transputers: A Study of Training Set Parallelism. To get started finding Parallel Implementations of Backpropagation Neural Networks on Transputers: A Study of Training Set Parallelism, you are right to find our website which has a comprehensive collection of manuals listed. Our library is the biggest of these that have literally hundreds of thousands of different products represented.