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Journal of Statistical Physics

, Volume 62, Issue 3–4, pp 563–576 | Cite as

Finite-state neural networks. A step toward the simulation of very large systems

  • G. A. Kohring
Articles

Abstract

Neural networks composed of neurons withQ N states and synapses withQ states are studied analytically and numerically. Analytically it is shown that these finite-state networks are much more efficient at information storage than networks with continuous synapses. In order to take the utmost advantage of networks with finite-state elements, a multineuron and multisynapse coding scheme is introduced which allows the simulation of networks having 1.0×109 couplings at a speed of 7.1×109 coupling evaluations per second on asingle processor of the Cray-YMP. A local learning algorithm is also introduced which allows for the efficient training of large networks with finite-state elements.

Key words

Neural networks multi-spin coding replica method finite-state networks learning algorithms 

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Copyright information

© Plenum Publishing Corporation 1991

Authors and Affiliations

  • G. A. Kohring
    • 1
  1. 1.Höchstleistungsrechenzentrum an der KFA JülichJülichGermany

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