Silicon Implementation of Pulse Coded Neural Networks

. Ed(s): Zaghloul, Mona E.; Meador, Jack L. (Department of Electrical Engineering and Computer Science, George Washington University, USA); Newcomb,

ISBN 10: 0792394496 / ISBN 13: 9780792394495

Published by Kluwer Academic Publishers, 1994

About this Item

Presents state-of-the-art research results which address conventional abstract notions of neural-like processing, as well as the more specific details of neural-like processors. The text seeks to cover many of the relevant contemporary studies coming out of this newly emerging area. Editor(s): Zaghloul, Mona E.; Meador, Jack L. (Department of Electrical Engineering and Computer Science, George Washington University, USA); Newcomb, Robert W. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 301 pages, biography. BIC Classification: TJFC. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 19. Weight in Grams: 609. . 1994. 1994th Edition. hardcover. . . . .

Seller Inventory # V9780792394495

Bibliographic Details

• Title: Silicon Implementation of Pulse Coded Neural Networks
• Publisher: Kluwer Academic Publishers
• Publication Date: 1994
• Language: English
• ISBN 10: 0792394496
• ISBN 13: 9780792394495
• Binding: Hardcover
• Condition: New

About this title

Synopsis

When confronted with the hows and whys of nature's computational engines, some prefer to focus upon neural function: addressing issues of neural system behavior and its relation to natural intelligence. Then there are those who prefer the study of the "mechanics" of neural systems: the nuts and bolts of the "wetware": the neurons and synapses. Those who investigate pulse coded implementations ofartificial neural networks know what it means to stand at the boundary which lies between these two worlds: not just asking why natural neural systems behave as they do, but also how they achieve their marvelous feats. The research results presented in this book not only address more conventional abstract notions of neural-like processing, but also the more specific details ofneural-like processors. It has been established for some time that natural neural systems perform a great deal of information processing via electrochemical pulses. Accordingly, pulse coded neural network concepts are receiving increased attention in artificial neural network research. This increased interest is compounded by continuing advances in the field of VLSI circuit design. This is the first time in history in which it is practical to construct networks of neuron-like circuits of reasonable complexity that can be applied to real problems. We believe that the pioneering work in artificial neural systems presented in this book will lead to further advances that will not only be useful in some practical sense, but may also provide some additional insight into the operation of their natural counterparts.