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Global exponential robust stability of reaction–diffusion interval neural networks with continuously distributed delays

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Abstract

This paper considers the existence of the equilibrium point and its global exponential robust stability for reaction-diffusion interval neural networks with variable coefficients and distributed delays by means of the topological degree theory and Lyapunov-functional method. The sufficient conditions on global exponential robust stability established in this paper are easily verifiable. An example is presented to demonstrate the effectiveness and efficiency of our results.

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Acknowledgments

The authors would like to thank the Editor and the anonymous reviewers for their valuable comments and constructive suggestions. Moreover, this work was supported by the National Natural Science Foundations of China under grant no. 60973048 and 60974025 and the Science Foundation of Harbin Institute of Technology(Weihai)(HIT(WH)200807).

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Authors and Affiliations

  1. Department of Mathematics, Harbin Institute of Technology(Weihai), 264209, Shandong, China

    Yonggui Kao

  2. Department of Mathematics, Ocean University of China, 266071, Qingdao, China

    Cunchen Gao

  3. Department of Mathematics, North University of China, 030051, Shanxi, China

    Wei Han

Authors
  1. Yonggui Kao
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  2. Cunchen Gao
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  3. Wei Han
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Correspondence to Yonggui Kao.

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Kao, Y., Gao, C. & Han, W. Global exponential robust stability of reaction–diffusion interval neural networks with continuously distributed delays. Neural Comput & Applic 19, 867–873 (2010). https://doi.org/10.1007/s00521-010-0367-7

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  • DOI: https://doi.org/10.1007/s00521-010-0367-7

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