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Impulsive Stochastic BAM Neural Networks on an Invariant Under a Translation Time Scale

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Abstract

Since the definition of \(p\)-mean almost periodic functions on time scales occupies a fundamental position in studying \(p\)-mean almost periodicity for stochastic neural networks, a concept of \(p\)-mean almost periodic functions on an invariant under a translation time scale is introduced for the first time in this paper. As an application, the existence and exponential stability of piecewise mean-square almost periodic solutions for a class of high-order BAM neural networks on time scales is studied by using the contraction mapping principal and differential inequality techniques. Finally, a numerical example is presented to illustrate the feasibility of our main results.

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Acknowledgements

Thanks to editors and anonymous reviewers for our manuscript.

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Authors and Affiliations

  1. Yunnan Minzu University, Kunming, Yunnan, 650500, People’s Republic of China

    Wanqin Wu

  2. School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, Yunnan, 650221, People’s Republic of China

    Li Yang

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  1. Wanqin Wu
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  2. Li Yang
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Correspondence to Li Yang.

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This work is supported by Tian Yuan Fund of NSFC (No. 11526180), Yunnan Province Education Department Scientific Research Fund Project (No. 2018JS315, No. 2018JS309).

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Wu, W., Yang, L. Impulsive Stochastic BAM Neural Networks on an Invariant Under a Translation Time Scale. Acta Appl Math 169, 647–665 (2020). https://doi.org/10.1007/s10440-020-00316-y

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