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Anti-periodic solutions for HCNNs with time-varying delays in the leakage terms

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Abstract

In this paper, a class of high-order cellular neural networks model is considered with the introduction of time-varying delays in the leakage terms. By using differential inequality techniques, some very verifiable and practical delay-dependent criteria on the existence and global exponential stability of anti-periodic solution for the model are derived. Even for the model without leakage delays, the criteria are shown to be less conservative than many recent publications. Moreover, some examples and remarks are given to demonstrate the feasibility of our method.

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Acknowledgments

The authors would like to express the sincere appreciation to the reviewers for their helpful comments in improving the presentation and quality of the paper. In particular, the authors expresses the sincere gratitude to Prof. Bingwen Liu for the helpful discussion when this work is carried out. This work was supported by the Construct Program of the Key Discipline in Hunan Province, the Science and Technology Planning project of Technology Department of Hunan Province (Grant no. 2012FJ4300), the Science and Technology Planning project of Chenzhou City in Hunan Province (Grant no. [2011]29), and the Natural Scientific Research Fund of Hunan Provincial Education Department (Grant no. 11C1186).

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  1. Department of Mathematics, Xiangnan College, Chenzhou, 423000, Hunan, People’s Republic of China

    Yanli Xu

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  1. Yanli Xu
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Correspondence to Yanli Xu.

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Xu, Y. Anti-periodic solutions for HCNNs with time-varying delays in the leakage terms. Neural Comput & Applic 24, 1047–1058 (2014). https://doi.org/10.1007/s00521-012-1330-6

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  • DOI: https://doi.org/10.1007/s00521-012-1330-6

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