Synergetic Computers and Cognition

A Top-Down Approach to Neural Nets

  • Hermann Haken

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

Table of contents

  1. Front Matter
    Pages I-IX
  2. Goal

    1. Hermann Haken
      Pages 1-6
  3. Synergetic Computers

    1. Front Matter
      Pages 7-7
    2. Hermann Haken
      Pages 9-17
    3. Hermann Haken
      Pages 18-19
    4. Hermann Haken
      Pages 20-35
    5. Hermann Haken
      Pages 56-59
    6. Hermann Haken
      Pages 88-124
    7. Hermann Haken
      Pages 125-133
  4. Cognition and Synergetic Computers

  5. Logical Operations and Outlook

    1. Front Matter
      Pages 203-203
    2. Hermann Haken
      Pages 209-230
    3. Hermann Haken
      Pages 231-233
  6. Back Matter
    Pages 235-245

About this book


This book presents a novel approach to neural nets and thus offers a genuine alternative to the hitherto known neuro-computers. This approach is based on the author's discovery of the profound analogy between pattern recognition and pattern formation in open systems far from equilibrium. Thus the mathematical and conceptual tools of synergetics can be exploited, and the concept of the synergetic computer formulated. A complete and rigorous theory of pattern recognition and learning is presented. The resulting algorithm can be implemented on serial computers or realized by fully parallel nets whereby no spurious states occur. Explicit examples (recognition of faces and city maps) are provided. The recognition process is made invariant with respect to simultaneous translation, rotation, and scaling, and allows the recognition of complex scenes. Oscillations and hysteresis in the perception of ambiguous patterns are treated, as well as the recognition of movement patterns. A comparison between the recognition abilities of humans and the synergetic computer sheds new light on possible models of mental processes. The synergetic computer can also perform logical steps such as the XOR operation. The new edition includes a section on transformation properties of the equations of the synergetic computer and on the invariance properties of the order parameter equations. Further additions are a new section on stereopsis and recent developments in the use of pulse-coupled neural nets for pattern recognition.


Neuro computers Parallel computers Puls-Coupled Neural Networks Stereo Stereopsis Synergetic Computer Synergetics cognition learning

Authors and affiliations

  • Hermann Haken
    • 1
  1. 1.Institut für Theoretische Physik und SynergetikUniversität StuttgartStuttgartGermany

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2004
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-07573-5
  • Online ISBN 978-3-662-10182-7
  • Series Print ISSN 0172-7389
  • Buy this book on publisher's site
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