Collective Phenomena in Neural Networks

  • J. Leo van Hemmen
  • Reimer Kühn
Part of the Physics of Neural Networks book series (NEURAL NETWORKS)

Synopsis and Note

In this paper we review some central notions of the theory of neural networks. In so doing we concentrate on collective aspects of the dynamics of large networks. The neurons are usually taken to be formal but this is not a necessary requirement for the central notions to be applicable. Formal neurons just make the theory simpler.

There are at least two ways of reading this review. It may be read as a self-contained introduction to the theory of neural networks. Alternatively, one may regard it as a vade mecum that goes with the other articles in the present book and may be consulted if one needs further explanation or meets an unknown idea. In order to allow the second approach as well we have tried to keep the level of redundancy much higher than is strictly necessary. So the attentive reader should not be annoyed if (s)he notices that some arguments are repeated.

Equations are labeled by (x.y.z). Referring to an equation within a subsection we only mention (z), within a section (y.z), and elsewhere in the paper (x.y.z). The chapter number is ignored.

The article also contains some new and previously unpublished results.


Hebbian Learning Synaptic Efficacy Sublattice Magnetization Glauber Dynamic Retrieval State 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • J. Leo van Hemmen
  • Reimer Kühn

There are no affiliations available

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