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Publication:

An advantage of chaotic neural dynamics (2007)

Author(s): Andras P, Lycett S

    Abstract: One hypothesis about how biological neural systems work suggests that they use attractor dynamics to define their behaviour. Such behaviour can be modelled using recurrent neural network models. It has been shown that such systems can perform a wide range of computational tasks by learning abstract grammars. Here we show that chaotic neural dynamics in recurrent neural systems is advantageous in the sense that it facilitates the encoding of grammars describing complex behaviour. This result may explain why it is common the observation of chaotic dynamics in biological neural systems.

      • Date: 12-17 August 2007
      • Conference Name: Proceedings of the International Joint Conference on Neural Networks (IJCNN)
      • Pages: 1417-1422
      • Publisher: IEEE
      • Publication type: Conference Proceedings (inc. abstract)
      • Bibliographic status: Published

      Keywords: nonlinear dynamics, chaos, neural system, information encoding, attractor

      Staff

      Dr Peter Andras
      Reader in Complex Systems