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New stability results for delayed neural networks with data packet dropouts

Author

Listed:
  • Cai, Xiao
  • Zhong, Shouming
  • Wang, Jun
  • Shi, Kaibo

Abstract

This paper further investigates the stability analysis of delayed neural networks (DNNs) with data packet dropouts. Firstly, the delay-product-type function method is introduced to construct a suitable Lyapunov–Krasovskii functional (LKF) with delay-dependent matrices, which fully considers the integral terms, non-integral terms and time-delay correlation terms. Then, by applying free-matrix-base inequality (FMBI) and other valid inequalities mathematical analysis techniques, new stability criteria are established. Meanwhile, by solving a set of linear matrix inequalities (LMIs), the corresponding controllers are designed to ensure the system state stabilization. Finally, two examples are given to demonstrate the validity and feasibility of the proposed method.

Suggested Citation

  • Cai, Xiao & Zhong, Shouming & Wang, Jun & Shi, Kaibo, 2020. "New stability results for delayed neural networks with data packet dropouts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    • Handle: RePEc:eee:phsmap:v:555:y:2020:i:c:s0378437120303630
    DOI: 10.1016/j.physa.2020.124727
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    References listed on IDEAS

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    1. Wang, Jun & Shi, Kaibo & Huang, Qinzhen & Zhong, Shouming & Zhang, Dian, 2018. "Stochastic switched sampled-data control for synchronization of delayed chaotic neural networks with packet dropout," Applied Mathematics and Computation, Elsevier, vol. 335(C), pages 211-230.
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