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Existence and Global Exponential Stability of Pseudo Almost Periodic Solutions of a General Delayed BAM Neural Networks

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Abstract

This paper studies a class of general BAM neural networks with multiple delays. Employing the exponential dichotomy theory and fixed point method, together with constructing suitable Lyapunov functionals, easily verifiable delay-independent criteria are established to ensure the existence and global exponential stability of pseudo almost periodic solutions, which not only generalize but also complement some existing ones. These theoretical results are also supported with numerical simulations.

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Acknowledgements

The author would like to express the sincere appreciation to the editor and reviewer for their helpful comments in improving the presentation and quality of the paper. In particular, the author expresses the sincere gratitude to Prof. LI Dequan for the helpful discussion when this revision work was being carried out.

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Authors and Affiliations

  1. School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, 232001, China

    Lian Duan

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  1. Lian Duan
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Correspondence to Lian Duan.

Additional information

This work was supported by the National Natural Science Foundation of China under Grant No. 11701007, Key Program of University Natural Science Research Fund of Anhui Province under Grant No. KJ2017A088, Key Program of Scientific Research Fund for Young Teachers of Anhui University of Science and Technology under Grant No. QN201605 and the Doctoral Fund of Anhui University of Science and Technology under Grant No. 11668.

This paper was recommended for publication by Editor SUN Jian.

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Duan, L. Existence and Global Exponential Stability of Pseudo Almost Periodic Solutions of a General Delayed BAM Neural Networks. J Syst Sci Complex 31, 608–620 (2018). https://doi.org/10.1007/s11424-017-6180-y

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  • DOI: https://doi.org/10.1007/s11424-017-6180-y

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