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New algebraic conditions for ISS of memristive neural networks with variable delays

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Abstract

In this paper, a general class of memristive neural networks with variable delays is studied. By utilizing control theory and nonsmoooth analysis, two sufficient criteria ensuring input-to-state stability of memristive neural networks with variable delays are firstly obtained which are novel and more practical than the previous works in the literature. Finally, a numerical example is given to demonstrate the effectiveness of our results.

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Acknowledgments

The authors would like to thank the editor and the anonymous reviewers for their insightful comments and valuable suggestions, which have helped us in finalizing the paper. This work was supported by the Fundamental Research Funds for the Central Universities of 2015QNA55.

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Authors and Affiliations

  1. College of Sciences, China University of Mining and Technology, Xuzhou, 221116, China

    Kai Zhong, Qiqi Yang & Song Zhu

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  1. Kai Zhong
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  2. Qiqi Yang
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  3. Song Zhu
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Correspondence to Kai Zhong.

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Zhong, K., Yang, Q. & Zhu, S. New algebraic conditions for ISS of memristive neural networks with variable delays. Neural Comput & Applic 28, 2089–2097 (2017). https://doi.org/10.1007/s00521-016-2176-0

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  • DOI: https://doi.org/10.1007/s00521-016-2176-0

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