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Exponential stability for the neutral-type singular neural network with time-varying delays

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Abstract

This paper deals with the problem of global exponential stability for neutral type singular networks with time-varying delays. Delay-dependent criterion is proposed to guarantee the exponential stability of neutral type singular networks via linear matrix inequality (LMI) approach. Improved global exponential stability condition is derived by employing a new Lyapunov–Krasovskii functional and a rarely integral inequality. The developed result is less conservative than previous published ones in the literature, which is illustrated by representative numerical examples.

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Acknowledgements

This paper is supported by the National Natural Science Foundation of China (No. 61273004) and the Natural Science Foundation of Hebei Province (No. F2014203085).

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Authors and Affiliations

  1. College of Science, Yanshan University, Qinhuangdao, 066004, China

    Yuechao Ma, Nannan Ma & Yu Han

  2. College of Science, Southwest Petroleum University, Chengdu, 610500, China

    Lin Chen

  3. College of Electrical Engineering, Tianjin University, Tianjin, 300072, China

    Yuqing Zheng

Authors
  1. Yuechao Ma
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  2. Nannan Ma
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  3. Lin Chen
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  4. Yuqing Zheng
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  5. Yu Han
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Correspondence to Nannan Ma.

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Ma, Y., Ma, N., Chen, L. et al. Exponential stability for the neutral-type singular neural network with time-varying delays. Int. J. Mach. Learn. & Cyber. 10, 853–858 (2019). https://doi.org/10.1007/s13042-017-0764-7

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  • DOI: https://doi.org/10.1007/s13042-017-0764-7

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