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Global asymptotical stability for a class of non-autonomous impulsive inertial neural networks with unbounded time-varying delay

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Abstract

This article is concerned with the global asymptotical stability of non-autonomous impulsive inertial neural networks with unbounded delay. A new impulsive differential delay inequality which involves unbounded and non-differential delay is established. Moreover, based on a new impulsive differential delay inequality, new analysis techniques can effectively avoid the difficulties caused by unbounded delay and impulses, and several novel delay-dependent inequalities are obtained to ensure the global stability of this model. In the end, three examples are given to claim the validity of theoretical analysis.

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Acknowledgements

This work was supported by National Natural Science Foundation of People’s Republic of China (Grant Nos. 61633011,61703346, 61374078), Graduate Student Research Innovation Project of Chongqing (Projet No. CYB17076).

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Authors and Affiliations

  1. National and Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology (Chongqing), College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, People’s Republic of China

    Hongfei Li, Wei Zhang, Chuandong Li & Wanli Zhang

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  1. Hongfei Li
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  2. Wei Zhang
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  3. Chuandong Li
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  4. Wanli Zhang
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Correspondence to Chuandong Li.

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Li, H., Zhang, W., Li, C. et al. Global asymptotical stability for a class of non-autonomous impulsive inertial neural networks with unbounded time-varying delay. Neural Comput & Applic 31, 6757–6766 (2019). https://doi.org/10.1007/s00521-018-3498-x

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  • DOI: https://doi.org/10.1007/s00521-018-3498-x

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