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Exponential synchronization of delayed Markovian jump complex networks with generally uncertain transition rates

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  • Xu, Ruiping
  • Kao, Yonggui
  • Gao, Cunchen

Abstract

This paper investigates the exponential synchronization problem for a class of Markovian jump complex networks(MJCNs) with generally uncertain transition rates(GUTRs). In this GUTR neural network model, each transition rate can be completely unknown or only its estimate value is known. This new uncertain model could be applied to many practical cases. Based on the Lyapunov functional method and Kronecker product technique, a sufficient condition on the exponentially synchronization in mean square is derived in terms of linear matrix inequalities (LMIs)-which can be easily solved by using the Matlab LMI toolbox. Finally, one numerical example is well-studied to illustrate the effectiveness of the developed method.

Suggested Citation

  • Xu, Ruiping & Kao, Yonggui & Gao, Cunchen, 2015. "Exponential synchronization of delayed Markovian jump complex networks with generally uncertain transition rates," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 682-693.
    • Handle: RePEc:eee:apmaco:v:271:y:2015:i:c:p:682-693
    DOI: 10.1016/j.amc.2015.09.032
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    References listed on IDEAS

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    Cited by:

    1. Liang, Kun & Dai, Mingcheng & Shen, Hao & Wang, Jing & Wang, Zhen & Chen, Bo, 2018. "L2−L∞ synchronization for singularly perturbed complex networks with semi-Markov jump topology," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 450-462.
    2. Yan, Zhiguo & Song, Yunxia & Liu, Xiaoping, 2018. "Finite-time stability and stabilization for Itô-type stochastic Markovian jump systems with generally uncertain transition rates," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 512-525.

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