Chaotic Neural Network with Time Delay term for Sequential Patterns

  • Authors:

  • Kazuki Hirozawa;Yuko Osana

  • Affiliations:

  • Tokyo University of Technology, Hachiouji, Tokyo, Japan;Tokyo University of Technology, Hachiouji, Tokyo, Japan

  • Venue:
  • AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
  • Year:
  • 2008

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Abstract

In this paper, we propose a Chaotic Neural Network with Time Delay term for Sequential Patterns (CNNTDSP). The proposed model is based on the conventional chaotic neural network and has two types of connection weights; (1) normal weights for hetero associations and (2) weights with time delay for auto associations. The proposed model deal with the sequential patterns. In the proposed model, associations of the sequential pattern in short term and dynamic associations between sequential patterns in long term are realized. We carried out a series of computer experiments and confirmed the effectiveness of the proposed model.