Applied Mathematics and Mechanics (English Edition) ›› 2003, Vol. 24 ›› Issue (8): 989-996.

• 论文 • 上一篇    

CHAOS IN TRANSIENTLY CHAOTIC NEURAL NETWORKS

阮炯, 赵维锐, 刘荣颂   

  1. Department of Mathematics, Research Center for Nonlinear Science and Laboratory of Mathematics for Nonlinear Science, Fudan University, Shanghai 200433, P. R. China
  • 收稿日期:2001-11-27 修回日期:2002-04-17 出版日期:2003-08-18 发布日期:2003-08-18
  • 基金资助:
    the National Natural Science Foundation of China(70271065)

CHAOS IN TRANSIENTLY CHAOTIC NEURAL NETWORKS

RUAN Jiong, ZHAO Wei-rui, LIU Rong-song   

  1. Department of Mathematics, Research Center for Nonlinear Science and Laboratory of Mathematics for Nonlinear Science, Fudan University, Shanghai 200433, P. R. China
  • Received:2001-11-27 Revised:2002-04-17 Online:2003-08-18 Published:2003-08-18
  • Supported by:
    the National Natural Science Foundation of China(70271065)

摘要: It was theoretically proved that one-dimensional transiently chaotic neural networks have chaotic structure in sense of Li-Yorke theorem with some given assumptions using that no division implies chaos. In particular, it is further derived sufficient conditions for the existence of chaos in sense of Li-Yorke theorem in chaotic neural network, which leads to the fact that Aihara has demonstrated by numerical method. Finally, an example and numerical simulation are shown to illustrate and reinforce the previous theory.

Abstract: It was theoretically proved that one-dimensional transiently chaotic neural networks have chaotic structure in sense of Li-Yorke theorem with some given assumptions using that no division implies chaos. In particular, it is further derived sufficient conditions for the existence of chaos in sense of Li-Yorke theorem in chaotic neural network, which leads to the fact that Aihara has demonstrated by numerical method. Finally, an example and numerical simulation are shown to illustrate and reinforce the previous theory.

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