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Weak attractor for stochastic Cohen–Grossberg neural networks with delays

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Abstract

This paper investigates a weak attractor for stochastic Cohen–Grossberg neural networks with delays. By employing the Lyapunov method and Lasalle-type theorem, novel results, and sufficient criteria on the weak attractor are obtained.

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Authors and Affiliations

  1. Department of Mathematics and Physics, Wuhan Textile University, Wuhan, 430073, China

    Li Wan

  2. Department of Mathematics, Zhaoqing University, Zhaoqing, 526061, China

    Qinghua Zhou

  3. School of Mathematics and Statistics, Wuhan University, Wuhan, 430072, China

    Pei Wang

Authors
  1. Li Wan
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  2. Qinghua Zhou
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  3. Pei Wang
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Correspondence to Li Wan.

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Wan, L., Zhou, Q. & Wang, P. Weak attractor for stochastic Cohen–Grossberg neural networks with delays. Nonlinear Dyn 67, 1753–1759 (2012). https://doi.org/10.1007/s11071-011-0103-6

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  • DOI: https://doi.org/10.1007/s11071-011-0103-6

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