Parallel Architectures For Artificial Neural Net- Works Paradigms & Implementations

An excellent reference for neural networks research and application, this book covers the parallel implementation aspects of all major artificial neural network models in a single text. "Parallel Architectures for Artificial Neural Networks" details implementations on various processor architectures built on different hardware platforms, ranging from large, general purpose parallel computers to custom built MIMD machine.

Working experts describe their implementation research including results that are then divided into three sections: The theoretical analysis of parallel implementation schemes on MIMD message passing machinesThe details of parallel implementation of BP neural networks on general purpose, large, parallel computersFour specific purpose parallel neural computer configuration

Aimed at graduate students and researchers working in artificial neural networks and parallel computing this work can be used by graduate level educators to illustrate parallel computing methods for ANN simulation. Practitioners will also find the text an ideal reference tool for lucid mathematical analyses.

This excellent reference for all those involved in neural networks research and application presents, in a single text, the necessary aspects of parallel implementation for all major artificial neural network models. The book details implementations on varoius processor architectures (ring, torus, etc.) built on different hardware platforms, ranging from large general purpose parallel computers to custom built MIMD machines using transputers and DSPs.
Experts who performed the implementations author the chapters and research results are covered in each chapter. These results are divided into three parts.
Theoretical analysis of parallel implementation schemes on MIMD message passing machines.
Details of parallel implementation of BP neural networks on a general purpose, large, parallel computer.
Four chapters each describing a specific purpose parallel neural computer configuration.
This book is aimed at graduate students and researchers working in artificial neural networks and parallel computing. Graduate level educators can use it to illustrate the methods of parallel computing for ANN simulation. The text is an ideal reference providing lucid mathematical analyses for practitioners in the field.