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New Stability Criterion for Takagi-Sugeno Fuzzy Cohen-Grossberg Neural Networks with Probabilistic Time-Varying Delays

Author

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  • Xiongrui Wang
  • Ruofeng Rao
  • Shouming Zhong

Abstract

A new global asymptotic stability criterion of Takagi-Sugeno fuzzy Cohen-Grossberg neural networks with probabilistic time-varying delays was derived, in which the diffusion item can play its role. Owing to deleting the boundedness conditions on amplification functions, the main result is a novelty to some extent. Besides, there is another novelty in methods, for Lyapunov-Krasovskii functional is the positive definite form of powers, which is different from those of existing literature. Moreover, a numerical example illustrates the effectiveness of the proposed methods.

Suggested Citation

  • Xiongrui Wang & Ruofeng Rao & Shouming Zhong, 2017. "New Stability Criterion for Takagi-Sugeno Fuzzy Cohen-Grossberg Neural Networks with Probabilistic Time-Varying Delays," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-11, November.
    • Handle: RePEc:hin:jnlmpe:3793157
    DOI: 10.1155/2017/3793157
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    Cited by:

    1. Xiongrui Wang & Ruofeng Rao & Shouming Zhong, 2020. "p th Moment Stability of a Stationary Solution for a Reaction Diffusion System with Distributed Delays," Mathematics, MDPI, vol. 8(2), pages 1-10, February.

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