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Almost Automorphic Solutions for Fuzzy Cohen-Grossberg Neural Networks with Mixed Time Delays

机译:具有混合时滞的模糊Cohen-Grossberg神经网络的概亚纯解

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摘要

This paper is concerned with the problem of almost automorphic solutions of a class of fuzzyCohen-Grossberg neural networks with mixed time delays and variable coefficients. Based on inequality analysis techniques and combining the exponential dichotomy with fixed point theorem, some sufficient conditions for the existence and global exponential stability of almost automorphic solutions are obtained. Finally, a numerical example is given to show the feasibility of our results.
机译:本文关注的是一类具有混合时滞和可变系数的模糊Cohen-Grossberg神经网络的几乎自纯解的问题。在不等式分析技术的基础上,将指数二分法与不动点定理相结合,为几乎自同构解的存在和全局指数稳定性提供了一些充分的条件。最后,通过数值例子说明了我们的结果的可行性。

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  • 来源
    《Mathematical Problems in Engineering 》 |2015年第4期| 812670.1-812670.14| 共14页
  • 作者单位

    Yunnan Univ, Dept Math, Kunming 650091, Yunnan, Peoples R China.;

    Yunnan Univ, Dept Math, Kunming 650091, Yunnan, Peoples R China.;

    Qujing Normal Univ, Sch Mathamat & Informat Sci, Qujing 655011, Yunnan, Peoples R China.;

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