Parallel Architectures ANNs
| AUTHOR | Saratchandran, P.; Sundararajan, N.; Saratchandran et al. |
| PUBLISHER | Wiley-IEEE Computer Society PR (12/14/1998) |
| PRODUCT TYPE | Hardcover (Hardcover) |
Description
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.
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.
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Product Format
Product Details
ISBN-13:
9780818683992
ISBN-10:
0818683996
Binding:
Hardback or Cased Book (Sewn)
Content Language:
English
More Product Details
Page Count:
412
Carton Quantity:
10
Product Dimensions:
7.30 x 1.09 x 10.39 inches
Weight:
1.95 pound(s)
Feature Codes:
Index,
Table of Contents,
Illustrated
Country of Origin:
US
Subject Information
BISAC Categories
Computers | Data Science - Neural Networks
Computers | Distributed Systems - General
Computers | Computer Engineering
Dewey Decimal:
006.32
Library of Congress Control Number:
98-22934
Descriptions, Reviews, Etc.
jacket back
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 machines
- The details of parallel implementation of BP neural networks on general purpose, large, parallel computers
- Four 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.
Show More
publisher marketing
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.
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.
Show More
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