Silicon Implementation of Pulse Coded Neural Networks

  • Mona E. Zaghloul
  • Jack L. Meador
  • Robert W. Newcomb

Table of contents

  1. Front Matter
    Pages i-ix
  2. Alan F. Murray
    Pages 9-37
  3. John G. Elias
    Pages 39-63
  4. Jack L. Meador, Paul D. Hylander
    Pages 79-99
  5. Marc de Savigny, Robert W. Newcomb
    Pages 101-111
  6. John Lazzaro, John Wawrzynek
    Pages 153-164
  7. Bernabé Linares-Barranco, Edgar Sánchez-Sinencio, Angel Rodríguez-Vázquez, José L. Huertas
    Pages 199-247
  8. Gamze E. Salam, Rodney M Goodman
    Pages 249-261
  9. James Donald, Lex A. Akers
    Pages 263-290
  10. Back Matter
    Pages 291-292

About this book


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.


CMOS Modulation VLSI complexity information integrated circuit static-induction transistor

Editors and affiliations

  • Mona E. Zaghloul
    • 1
  • Jack L. Meador
    • 2
  • Robert W. Newcomb
    • 3
  1. 1.The George Washington UniversityUSA
  2. 2.Washington State UniversityUSA
  3. 3.University of MarylandUSA

Bibliographic information

  • DOI
  • Copyright Information Kluwer Academic Publishers 1994
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-6152-7
  • Online ISBN 978-1-4615-2680-3
  • Series Print ISSN 0893-3405
  • Buy this book on publisher's site