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Exponential \(p\)-Synchronization of Non-autonomous Cohen–Grossberg Neural Networks with Reaction-Diffusion Terms via Periodically Intermittent Control

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Abstract

The problem of \(p\)-synchronization for a class of stochastic non-autonomous reaction-diffusion Cohen–Grossberg networks with mixed delays by using periodically intermittent feedback control is investigated in this paper. Some exponential synchronization criteria based on \(p\)-norm are obtained by utilizing some analysis methods. These proofs indirectly generalized the Halanay inequality and facilitated the proof processing of the existing works. Finally, an illustrative example is given to show the effectiveness of the theoretical results.

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Acknowledgments

Supported by the National Natural Science Foundation of China (Grant Nos. 61174216 and 61074091), Graduate Scientific Research Creative Foundation of China Three Gorges University (No. 2011CX079) and the Natural Science Foundation of Hubei Province (2010CDB1080), and the Science Foundation of Education Commission of Hubei Province (D20101202, D20101202).

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Authors and Affiliations

  1. College of Science, China Three Gorges University, Yichang, 443002, Hubei, China

    Jun Mei, Minghui Jiang, Bin Wang, Qing Liu, Wangming Xu & Tao Liao

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  1. Jun Mei
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  2. Minghui Jiang
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  3. Bin Wang
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  4. Qing Liu
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  5. Wangming Xu
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  6. Tao Liao
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Correspondence to Jun Mei.

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Mei, J., Jiang, M., Wang, B. et al. Exponential \(p\)-Synchronization of Non-autonomous Cohen–Grossberg Neural Networks with Reaction-Diffusion Terms via Periodically Intermittent Control. Neural Process Lett 40, 103–126 (2014). https://doi.org/10.1007/s11063-013-9313-x

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