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Global Robust Attractive and Invariant Sets of Fuzzy Neural Networks with Delays and Impulses

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  • Kaihong Zhao
  • Liwenjing Wang
  • Juqing Liu

Abstract

A class of fuzzy neural networks (FNNs) with time-varying delays and impulses is investigated. With removing some restrictions on the amplification functions, a new differential inequality is established, which improves previouse criteria. Applying this differential inequality, a series of new and useful criteria are obtained to ensure the existence of global robust attracting and invariant sets for FNNs with time-varying delays and impulses. Our main results allow much broader application for fuzzy and impulsive neural networks with or without delays. An example is given to illustrate the effectiveness of our results.

Suggested Citation

  • Kaihong Zhao & Liwenjing Wang & Juqing Liu, 2013. "Global Robust Attractive and Invariant Sets of Fuzzy Neural Networks with Delays and Impulses," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-8, March.
    • Handle: RePEc:hin:jnljam:935491
    DOI: 10.1155/2013/935491
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