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Stability of Hopfield neural networks with time delays and variable-time impulses

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Abstract

The stability of Hopfield neural networks with fixed-time impulses has been intensively investigated in recent years. However, few existing publications addressed the stability of delayed neural networks with variable-time impulses. In this paper, we consider the case of variable-time impulses and attempt to establish the general stability criteria. It shows that the proposed results can also be applied to the case of fixed-time impulses, which provide a new stability condition for the case of fixed-time impulses. To illustrate the effectiveness of our theoretical results, numerical examples and simulations are also presented.

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Acknowledgments

The authors are grateful to the associate editor and reviewers for their constructive comments based on which the presentation of the paper has been greatly improved. The work described in this paper was partially supported by the Fundamental Research Funds for the Central Universities of China (Project No. CDJZR10 18 55 01) and National Natural Science Foundation of China (Grant No.60974020).

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Authors and Affiliations

  1. College of Computer, Chongqing University, Chongqing, 400044, People’s Republic of China

    Chao Liu, Chuandong Li & Chaojie Li

  2. Texas A&M University at Qatar, Doha, P.O. Box 23874, Qatar

    Tingwen Huang

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  1. Chao Liu
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  2. Chuandong Li
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Correspondence to Chuandong Li.

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Liu, C., Li, C., Huang, T. et al. Stability of Hopfield neural networks with time delays and variable-time impulses. Neural Comput & Applic 22, 195–202 (2013). https://doi.org/10.1007/s00521-011-0695-2

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