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Synergetic Computers and Cognition

A Top-Down Approach to Neural Nets

  • Textbook
  • © 1991

Overview

Authors:
  1. Hermann Haken

    1. Institut für Theoretische Physik und Synergetik, Universität Stuttgart, Stuttgart 80, Fed. Rep. of Germany
      Center for Complex Systems, Florida Atlantic University, Boca Raton, USA

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Part of the book series: Springer Series in Synergetics (SSSYN, volume 50)

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Table of contents (17 chapters)

  1. Front Matter

    Pages I-IX
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  2. Goal

    1. Goal

      • Hermann Haken
      Pages 1-6

  3. Synergetic Computers

    1. Front Matter

      Pages 7-7
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    2. What are Patterns?

      • Hermann Haken
      Pages 9-17

    3. Associative Memory

      • Hermann Haken
      Pages 18-19

    4. Synergetics — An Outline

      • Hermann Haken
      Pages 20-35

    5. The Standard Model of Synergetics for Pattern Recognition

      • Hermann Haken
      Pages 36-50

    6. Examples: Recognition of Faces and of City Maps

      • Hermann Haken
      Pages 51-55

    7. Possible Realizations by Networks

      • Hermann Haken
      Pages 56-59

    8. Simultaneous Invariance with Respect to Translation, Rotation and Scaling

      • Hermann Haken
      Pages 60-80

    9. Recognition of Complex Scenes. Scene-Selective Attention

      • Hermann Haken
      Pages 81-83

    10. Learning Algorithms

      • Hermann Haken
      Pages 84-120

    11. Learning of Processes and Associative Action

      • Hermann Haken
      Pages 121-129

  4. Cognition and Synergetic Computers

    1. Front Matter

      Pages 131-131
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    2. Comparisons Between Human Perception and Machine “Perception”

      • Hermann Haken
      Pages 133-148

    3. Oscillations in the Perception of Ambiguous Patterns

      • Hermann Haken
      Pages 149-170

    4. Dynamic Pattern Recognition of Coordinated Biological Motion

      • Hermann Haken
      Pages 171-188

  5. Logical Operations and Outlook

    1. Front Matter

      Pages 189-189
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    2. Realization of the Logical Operation XOR by a Synergetic Computer

      • Hermann Haken
      Pages 191-194

    3. Towards the Neural Level

      • Hermann Haken
      Pages 195-210
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Keywords

About this book

This book will be of interest to graduate students, researchers and teachers in the computer sciences, in the cognitive sciences andin physics. It provides the reader with a novel approach to the design and study of neural nets. The applicability of this approach is shown explicitly by means of realistic examples. In addition, detailed models of the cognitive abilities of humans are included and compared with the performance of the synergetic computer presented in this book. The work presented here would not have been possible without the important help of my coworkers. Dr. Arne Wunderlin has helped me in many respects over many years and has made essential contributions, in particular to the slaving principle of synergetics. Drs. Michael Bestehorn, Rudolf Friedrich and Wolfgang W eimer have applied the methods of synergetics to spontaneous pattern forma­ tion in fluids and have further developed these methods. Armirr Fuchs has not only implemented my algorithm on a VAX computer, but has also made his own important contributions, in particular to pattern recognition that is invariant with respect to translation, rotation, and scaling. Thomas Ditzinger, Richard Haas, and Robert Hönlinger have contributed within the work on their diploma theses to the application of our approach to a number of problems that are shared by humans and computers in the field of pattern recognition. I wish to thank all of them.

Authors and Affiliations

  • Institut für Theoretische Physik und Synergetik, Universität Stuttgart, Stuttgart 80, Fed. Rep. of Germany

    Hermann Haken

  • Center for Complex Systems, Florida Atlantic University, Boca Raton, USA

    Hermann Haken

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