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Improved delay-dependent stability criteria for neural networks with discrete and distributed time-varying delays using a delay-partitioning approach

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Abstract

This paper is focused on the problem of delay-dependent stability criteria for neural networks (NNs) with discrete and distributed time-varying delays. Firstly, by constructing a newly augmented Lyapunov–Krasovskii functionals with multiple integral terms, less conservative stability criteria are formulated in terms of linear matrix inequalities. Secondly, some improved delay-dependent stability results are obtained by dividing the discrete and distributed delays into multiple nonuniformly subintervals and using a novel activation function condition. Besides, by employing the idea of second-order convex combination and the property of quadratic convex function which has been not used in the previous papers of NNs with mixed time-varying delays, further improved delay-dependent stability conditions are proposed. Finally, two numerical examples are given to verify the effectiveness and superiority of our proposed main results.

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Authors and Affiliations

  1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Kaibo Shi, Hong Zhu, Yong Zeng & Yuping Zhang

  2. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Shouming Zhong

  3. Key Laboratory for Neuroinformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Shouming Zhong

Authors
  1. Kaibo Shi
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  2. Hong Zhu
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  3. Shouming Zhong
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  4. Yong Zeng
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  5. Yuping Zhang
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Corresponding author

Correspondence to Kaibo Shi.

Additional information

This work was supported by National Basic Research Program of China (2010CB732501), National Natural Science Foundation of China (61273015), The National Defense Scientific Research Project (9140A27040213DZ02001), The Program for New Century Excellent Talents in University (NCET-10-0097), The Fundamental Research Funds for the Central Universities under Grant 12NZYQN17, and Zhejiang Provincial Natural Science Foundation of China (LQ13A010023).

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Shi, K., Zhu, H., Zhong, S. et al. Improved delay-dependent stability criteria for neural networks with discrete and distributed time-varying delays using a delay-partitioning approach. Nonlinear Dyn 79, 575–592 (2015). https://doi.org/10.1007/s11071-014-1687-4

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  • DOI: https://doi.org/10.1007/s11071-014-1687-4

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