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Existence and Exponential Stability of Periodic Solution for BAM Fuzzy Cohen–Grossberg Neural Networks with Mixed Delays

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Abstract

In this paper, BAM fuzzy Cohen–Grossberg neural networks with mixed delays are considered. Using M-matrix theory and differential inequality techniques, some sufficient conditions for the existence and exponential stability of periodic solution to the neural networks are established. The results of this paper are completely new and complementary to the previously known results. Finally, an example is given to illustrate the effectiveness of our results obtained.

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Acknowledgments

The author would like to thank the editor and anonymous reviewers for their helpful comments and valuable suggestions, which have greatly improved the quality of this paper.

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Authors and Affiliations

  1. Faculty of Mathematics and Physics, Huaiyin Institute of Technology, Huai’an, 223003, Jiangsu, People’s Republic of China

    Hongmei Bao

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  1. Hongmei Bao
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Correspondence to Hongmei Bao.

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Bao, H. Existence and Exponential Stability of Periodic Solution for BAM Fuzzy Cohen–Grossberg Neural Networks with Mixed Delays. Neural Process Lett 43, 871–885 (2016). https://doi.org/10.1007/s11063-015-9455-0

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  • DOI: https://doi.org/10.1007/s11063-015-9455-0

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