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Weighted pseudo-anti-periodic SICNNs with mixed delays

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Abstract

A model of shunting inhibitory cellular neural networks with mixed delays is proposed. Applying appropriate differential inequality techniques, several sufficient conditions are derived to ensure the existence and exponential stability of weighted pseudo-anti-periodic solutions for the proposed neural networks. Moreover, numerical examples are provided to show the validity and the advantages of the obtained results

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Acknowledgments

The authors would like to express their sincere appreciation to the editor and reviewers for their helpful comments in improving the presentation and quality of the paper. In particular, the authors express the sincere gratitude to Prof. Bingwen Liu (Jiaxing University) for the helpful discussion when this revision work was being carried out. This work was supported by the Natural Scientific Research Fund of Hunan Province of China (Grant Nos. 2016JJ6103, 2016JJ6104).

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Authors and Affiliations

  1. College of Mathematics and Computer Science, Hunan University of Arts and Science, Changde, 415000, Hunan, People’s Republic of China

    Qiyuan Zhou

  2. College of Mathematics, Physics and Information Engineering, Jiaxing University, Jiaxing, 314001, Zhejiang, People’s Republic of China

    Jianying Shao

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  1. Qiyuan Zhou
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  2. Jianying Shao
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Correspondence to Jianying Shao.

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Zhou, Q., Shao, J. Weighted pseudo-anti-periodic SICNNs with mixed delays. Neural Comput & Applic 29, 865–872 (2018). https://doi.org/10.1007/s00521-016-2582-3

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  • DOI: https://doi.org/10.1007/s00521-016-2582-3

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