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Pseudo almost periodic solutions of discrete-time neutral-type neural networks with delays

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Abstract

This paper is concerned with discrete-time neutral-type neural networks with delays. The existence and uniqueness results of pseudo almost periodic solutions are established by applying the contraction mapping principal. By using some mathematical analysis techniques, we further obtain the boundness, exponential attractivity and global exponential stability of pseudo almost periodic solutions for the considered networks. Finally, a typical example and the corresponding numerical simulations have been carried out to support our analytic findings.

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Acknowledgements

The authors thank the anonymous reviewers for their insightful suggestions which improved this work significantly. This work was supported by the National Natural Science Foundation of China (Grant No.61572035).

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Authors and Affiliations

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

    Fanchao Kong & Xianwen Fang

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  1. Fanchao Kong
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  2. Xianwen Fang
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Correspondence to Fanchao Kong.

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Kong, F., Fang, X. Pseudo almost periodic solutions of discrete-time neutral-type neural networks with delays. Appl Intell 48, 3332–3345 (2018). https://doi.org/10.1007/s10489-018-1146-x

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