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Table of contents

  1. Front Matter
  2. Petr Lánsky, Vera Lánská
    Pages 49-54
  3. Christian W. Eurich, Hubert R. Dinse, Ulrike Dicke, Ben Godde, Helmut Schwegler
    Pages 55-60
  4. Simon Schultz, Stefano Panzeri, Alessandro Treves, Edmund T. Rolls
    Pages 61-66
  5. Maurizio Mattia, Stefano Fusi
    Pages 67-72
  6. Raphael Ritz, Terrence J. Sejnowski
    Pages 79-84
  7. J. Eggert, J. L. van Hemmen
    Pages 109-114
  8. Arjen van Ooyen, David J. Willshaw
    Pages 139-144
  9. Manuel Samuelides, Simon Thorpe, Emmanuel Veneau
    Pages 145-150
  10. Bruce Graham, David Willshaw
    Pages 151-156
  11. Christian W. Eurich, Jack D. Cowan, John G. Milton
    Pages 157-162
  12. M. Hübener, D. Shoham, S. Schulzel, G. Brändle, A. Grinvald, T. Bonhoeffer
    Pages 177-182
  13. Fred Wolf, Theo Geisel
    Pages 195-200
  14. Francesco Frisone, Luca Perico, Pietro G. Morasso
    Pages 201-206
  15. Ute Bauer, Péter Adorján, Michael Scholz, Jonathan B. Levitt, Jennifer S. Lund, Klaus Obermayer
    Pages 213-218
  16. Christian Ziegaus, Elmar W. Lang
    Pages 219-224
  17. Laurenz Wiskott, Terrence Sejnowski
    Pages 243-248
  18. Jinhui Chao, Miyata Yasuhiko, Shinich Yoshida
    Pages 255-260
  19. Vladimir N. Vapnik
    Pages 261-271
  20. Richard S. Sutton
    Pages 273-282
  21. Nathalie Chatenet, Hugues Bersini
    Pages 283-288
  22. N. P. Bradshaw, A. Duchâteau, H. Bersini
    Pages 295-300
  23. H. J. Kappen, F. B. Rodríguez
    Pages 301-306
  24. Maissa Aboukassem, Steffen Schwember, Steffen Noehte, Reinhard Männer
    Pages 313-318

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 7th International Conference on Artificial Neural Networks, ICANN'97, held in Lausanne, Switzerland,in October 1997. The 201 revised papers presented were selected from a large number of submissions and give a unique documentation of the state of the art in the area. The papers are organized in parts on coding and learning in biology; cortical maps and receptive fields; learning: theory and applications; signal processing: blind source separation, vector quantization, and self-organization; robotics, autonomous agents, and control; speech, vision and pattern recognition; prediction, forecasting and monitoring; and implementations.

Keywords

Controller Area Network (CAN) adaptive systems agents artificial neural network autonomous agents biocomputation cognition control learning neural networks pattern recognition robot robotics signal processing

Bibliographic information

  • DOI https://doi.org/10.1007/BFb0020124
  • Copyright Information Springer-Verlag Berlin Heidelberg 1997
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-63631-1
  • Online ISBN 978-3-540-69620-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site