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Parallel Architectures for Artificial Neural Networks: Paradigms and Implementations
N. Sundararajan; P. Saratchandran
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.

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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.