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Stochastic switched sampled-data control for synchronization of delayed chaotic neural networks with packet dropout

Author

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  • Wang, Jun
  • Shi, Kaibo
  • Huang, Qinzhen
  • Zhong, Shouming
  • Zhang, Dian

Abstract

This paper addresses the exponential synchronization issue of delayed chaotic neural networks (DCNNs) with control packet dropout. A novel stochastic switched sampled-data controller with time-varying sampling is developed in the frame of the zero-input strategy. First, by making full use of the available characteristics on the actual sampling pattern, a newly loop-delay-product-type Lyapunov–Krasovskii functional (LDPTLKF) is constructed via introducing a matrix-refined-function, which can reflect the information of delay variation. Second, based on the LDPTLKF and the relaxed Wirtinger-based integral inequality (RWBII), novel synchronization criteria are established to guarantee that DCNNs are synchronous exponentially when the control packet dropout occurs in a random way, which obeys certain Bernoulli distributed white noise sequences. Third, a desired sampled-data controller can be designed on account of the proposed optimization algorithm. Finally, the effectiveness and advantages of the obtained results are illustrated by two numerical examples with simulations.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:apmaco:v:335:y:2018:i:c:p:211-230
    DOI: 10.1016/j.amc.2018.04.038
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