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Robust dissipativity and passivity of stochastic Markovian switching CVNNs with probabilistic time-varying delay and partly unknown transition rates
  • Qiang Li,
  • Weiqiang Gong,
  • Linzhong Zhang
Qiang Li
Anhui Agricultural University
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Weiqiang Gong
Nanjing University of Finance and Economics - Xianlin Campus

Corresponding Author:[email protected]

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Linzhong Zhang
Anhui Agricultural University
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This paper is devoted to the robust dissipativity and passivity problems for Markovian switching complex-valued neural networks with probabilistic time-varying delay, where the transition rates are partly unknown, which might reflect more realistic dynamical behaviors of the switching networks. The probabilistic delay is described by a sequence of bernoulli distributed random variables, and mode-dependent parameter uncertainties are assumed to be norm-bounded. Based on the complex version of the generalized It$\hat{o}$’s formula, the robust analysis tools and the stochastic analysis methods, some sufficient mode/delay-dependent criteria on the $(M,N,W)$-dissipativity and passivity are derived in terms of complex matrix inequalities. In the end of paper, two numerical examples are presented to illustrate the effectiveness and feasibility of the obtained results.