© 1991

VLSI for Artificial Intelligence and Neural Networks

  • José G. Delgado-Frias
  • William R. Moore

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Architecture and Hardware Support for AI Processing

    1. Jean-Luc Bechennec, Christophe Chanussot, Vincent Neri, Daniel Etiemble
      Pages 1-10
    2. Hitoshi Aida, Sany Leinwand, José Meseguer
      Pages 11-22
    3. José Delgado-Frias, Ardsher Ahmed, Robert Payne
      Pages 23-32
    4. Yasunori Kimura, Takashi Chikayama, Tsuyoshi Shinogi, Atsuhiro Goto
      Pages 33-45
    5. Christian Hafer, Josef Plankl, Franz Josef Schmitt
      Pages 47-56
    6. Pratibha, P. Dasiewicz
      Pages 57-66
    7. Chang Jun Wang, Simon H. Lavington
      Pages 67-78
    8. Peter S. Sapaty
      Pages 79-91
    9. Lionel Tarassenko, Gillian Marshall, Felipe Gomez-Castaneda, Alan Murray
      Pages 93-99
  3. Machines for Prolog

    1. Pierluigi Civera, Evelina Lamma, Paola Mello, Antonio Natali, Gianluca Piccinini, Maurizio Zamboni
      Pages 109-119
    2. P. L. Civera, G. Masera, G. L. Piccinini, M. Ruo Roch, M. Zamboni
      Pages 121-131
    3. Alessandro De Gloria, Paolo Faraboschi, Elio Guidetti
      Pages 133-142
    4. Mark A. Friedman, Gurindar S. Sohi
      Pages 143-152
    5. Mario Cannataro, Giandomenico Spezzano, Domenico Talia
      Pages 165-174
  4. Analogue and Pulse Stream Neural Networks

    1. Chris Fields, Mark DeYong, Randall Findley
      Pages 175-184
    2. Christian Schneider, Howard Card
      Pages 185-194
    3. W. A. J. Waller, D. L. Bisset, P. M. Daniell
      Pages 195-204

About this book


This book is an edited selection of the papers presented at the International Workshop on VLSI for Artifidal Intelligence and Neural Networks which was held at the University of Oxford in September 1990. Our thanks go to all the contributors and especially to the programme committee for all their hard work. Thanks are also due to the ACM-SIGARCH, the IEEE Computer Society, and the lEE for publicizing the event and to the University of Oxford and SUNY-Binghamton for their active support. We are particularly grateful to Anna Morris, Maureen Doherty and Laura Duffy for coping with the administrative problems. Jose Delgado-Frias Will Moore April 1991 vii PROLOGUE Artificial intelligence and neural network algorithms/computing have increased in complexity as well as in the number of applications. This in tum has posed a tremendous need for a larger computational power than can be provided by conventional scalar processors which are oriented towards numeric and data manipulations. Due to the artificial intelligence requirements (symbolic manipulation, knowledge representation, non-deterministic computations and dynamic resource allocation) and neural network computing approach (non-programming and learning), a different set of constraints and demands are imposed on the computer architectures for these applications.


Hardware Symbol VLSI algorithm analog architecture artificial intelligence complexity computer computer architecture logic network neural network neural networks programming

Editors and affiliations

  • José G. Delgado-Frias
    • 1
  • William R. Moore
    • 2
  1. 1.State University of New York at BinghamtonBinghamtonUSA
  2. 2.Oxford UniversityOxfordUK

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