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Anti-Periodic Solutions for Shunting Inhibitory Cellular Neural Networks with Time-Varying Coefficients

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Abstract

This paper is concerned with the existence and exponential stability of anti-periodic solutions for shunting inhibitory cellular neural networks (SICNNs) with time-varying coefficients arising from the description of the neurons’ state in delayed neural networks. Some new sufficient conditions ensuring the existence and exponential stability of anti-periodic solutions for SICNNs are established.

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Authors and Affiliations

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

    Changhong Zhao & Qiyi Fan

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

    Wentao Wang

Authors
  1. Changhong Zhao
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  2. Qiyi Fan
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  3. Wentao Wang
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Correspondence to Wentao Wang.

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Zhao, C., Fan, Q. & Wang, W. Anti-Periodic Solutions for Shunting Inhibitory Cellular Neural Networks with Time-Varying Coefficients. Neural Process Lett 31, 259–267 (2010). https://doi.org/10.1007/s11063-010-9136-y

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  • DOI: https://doi.org/10.1007/s11063-010-9136-y

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