• Title/Summary/Keyword: Fuzzy BAM neural networks

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GLOBAL EXPONENTIAL STABILITY OF BAM FUZZY CELLULAR NEURAL NETWORKS WITH DISTRIBUTED DELAYS AND IMPULSES

  • Li, Kelin;Zhang, Liping
    • Journal of applied mathematics & informatics
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    • v.29 no.1_2
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    • pp.211-225
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    • 2011
  • In this paper, a class of bi-directional associative memory (BAM) fuzzy cellular neural networks with distributed delays and impulses is formulated and investigated. By employing an integro-differential inequality with impulsive initial conditions and the topological degree theory, some sufficient conditions ensuring the existence and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with distributed delays are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on the delay kernel functions and system parameters. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.

EXISTENCE AND GLOBALLY EXPONENTIAL STABILITY OF PERIODIC SOLUTION OF IMPULSIVE FUZZY BAM NEURAL NETWORKS WITH DISTRIBUTED DELAYS AND VARIABLE COEFFICIENTS

  • Zhang, Qianhong;Yang, Lihui;Liao, Daixi
    • Journal of applied mathematics & informatics
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    • v.30 no.5_6
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    • pp.1031-1049
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    • 2012
  • In this paper, a class of impulsive fuzzy bi-directional associative memory (BAM) neural networks with distributed delays and variable coefficients are considered. Using Lyapunov functional method and fixed point theorem, we derived some sufficient conditions for the existence and globally exponential stability of unique periodic solution of the networks. The results obtained are new and extend the previous known results. In addition, an example is given to show the effectiveness of our results obtained.