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Artificial Neural Networks

International Workshop IWANN '91, Granada, Spain, September 17-19, 1991. Proceedings

  • Conference proceedings
  • © 1991

Overview

Editors:
  1. Alberto Prieto
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 540)

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Table of contents (59 papers)

  1. Front Matter

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  2. Cooperative computing and neural networks

    • Panos A. Ligomenides
    Pages 1-10

  3. Neural Net's theory — The specifications of a computational model of memory and information processing in decision-making

    • José Mira y Mira, Roberto Moreno-Diaz, J. Simões da Fonseca
    Pages 11-16

  4. Chaotic neural networks and associative memory

    • T. Ikeguchi, M. Adachi, K. Aihara
    Pages 17-24

  5. Nonequilibrium model of neural networks

    • P. L. Garrido, J. Marro
    Pages 25-32

  6. A modified algorithm for self-organizing maps based on the Schrödinger equation

    • Tryba V, Goser K
    Pages 33-47

  7. Neural network modelling by means of networks of finite automata

    • Christel Kemke
    Pages 48-53

  8. Adaptive optimization of neural algorithms

    • C. Jutten, A. Guerin, H. L. Nguyen Thi
    Pages 54-61

  9. Neural networks with hysteresis type of nonlinearity exhibit global optimization property

    • J. Levendovszky, W. Mommaerts, E. C. van der Meulen
    Pages 62-68

  10. Stability measurement criterion for neural networks of competitive learning

    • Amparso Sacristán, Elena Valderrama, Conrado Pérez-Vicente
    Pages 69-77

  11. On the power of networks of majority functions

    • Eddy Mayoraz
    Pages 78-85

  12. Using quadratic perceptrons to reduce interconnection density in multilayer neural networks

    • Dirk Röckmann, Claudio Moraga
    Pages 86-92

  13. Always trying to write an equation for the brain

    • J. Mira, A. E. Delgado
    Pages 93-100

  14. Transformation of control signals for saccadic eye movements

    • Boris Breznen
    Pages 101-108

  15. On the semantics of morphogenesys in photoreceptors

    • K. N. Leibovic, R. Moreno-Diaz Jr.
    Pages 109-115

  16. Implementing a "psychophysical" pattern classifier in a decrementing network

    • José M. Salinas, Vernon G. Dobson
    Pages 116-123

  17. Contributions of Neural Net's Theory to the understanding of Psychopathological productions in Schizophrenia

    • J. Simões da Fonseca, J. Maltez, Isabel Barahona da Fonseca
    Pages 124-129

  18. Backpropagation growing networks: Towards local minima elimination

    • Ignacio Bellido, Gregorio Fernández
    Pages 130-135

  19. Methods for encoding in multilayer feed-forward neural networks

    • E. Elizalde, S. Gómez, A. Romeo
    Pages 136-143

  20. Learning algorithm for feed-forward neural networks with discrete synapses

    • C. J. Pérez Vicente, J. Carrabina, F. Garrido, E. Valderrama
    Pages 144-152
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Keywords

About this book

Artificial neural networks are massively parallel interconnected networks ofsimple elements which are intended to interact with the objects of the real world in the same way as biological nervous systems do. Interest in these networks is due to the opinion that they are able to perform tasks like image and speech recognition that have only been implemented in limited ways by traditional computing methods. This book includes invited lectures and the full contributions to the International Workshop onArtificial Neural Networks held in Granada, Spain, September 17-19, 1991. The workshop was sponsored by the IEEE Computer Society, the Spanish Association for Computing and Automatics, and the University of Granada. The contributions were selected by an international program committee; the authors of the papers come from 12 countries. The book is organized in six sections, covering: - Neural network theories and neural models - Biological perspectives - Neural network architectures and algorithms - Software developments and tools - Hardware implementations - Applications.

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