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Statistical physics of interacting neural networks

Author

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  • Kinzel, Wolfgang
  • Metzler, Richard
  • Kanter, Ido

Abstract

Recent results on the statistical physics of time series generation and prediction are presented. A neural network is trained on quasi-periodic and chaotic sequences and overlaps to the sequence generator as well as the prediction errors are calculated numerically. For each network there exists a sequence for which it completely fails to make predictions. Two interacting networks show a transition to perfect synchronization. A pool of interacting networks shows good coordination in the minority game—a model of competition in a closed market. Finally, as a demonstration, a perceptron predicts bit sequences produced by human beings.

Suggested Citation

  • Kinzel, Wolfgang & Metzler, Richard & Kanter, Ido, 2001. "Statistical physics of interacting neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 302(1), pages 44-55.
    • Handle: RePEc:eee:phsmap:v:302:y:2001:i:1:p:44-55
    DOI: 10.1016/S0378-4371(01)00443-5
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    Cited by:

    1. Groot, Robert D. & Musters, Pieter A.D., 2005. "Minority Game of price promotions in fast moving consumer goods markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 533-547.

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