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Pseudo S-Asymptotically \(\omega \)-Antiperiodic Solutions for SICNNs with Mixed Delays

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Abstract

In this paper, we mainly investigate pseudo S-asymptotically \(\omega \)-antiperiodic solutions to shunting inhibitory cellular neural networks (SICNNs) with mixed delays. After proving some auxiliary results, we first show the existence of pseudo S-asymptotically \(\omega \)-antiperiodic solutions to SICNNs and the convergence rate under local Lipschitz growth conditions on the signal transmission functions. We then establish the existence and uniqueness of pseudo S-asymptotically \(\omega \)-antiperiodic solutions and get the globally exponential stability under global Lipschitiz growth conditions on the signal transmission functions. We finally give an example with its numerical simulations to verify the main results.

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Acknowledgements

This work was partially supported by NSFC (12271419). Authors would like to thank anonymous referees and the editor for carefully reading this manuscript and giving valuable comments to improve the previous version of this paper.

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Authors and Affiliations

  1. School of Mathematics and Statistics, Xidian University, Xi’an, 710071, Shaanxi, People’s Republic of China

    Penghui Lü & Yong-Kui Chang

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  1. Penghui Lü
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  2. Yong-Kui Chang
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Correspondence to Yong-Kui Chang.

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Lü, P., Chang, YK. Pseudo S-Asymptotically \(\omega \)-Antiperiodic Solutions for SICNNs with Mixed Delays. Neural Process Lett 55, 5401–5423 (2023). https://doi.org/10.1007/s11063-022-11091-2

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