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This paper is concerned with the problem of exponential stability for a class of Markovian jump impulsive stochastic Cohen-Grossberg neural networks with mixed time delays and known or unknown parameters. The jumping parameters are determined by a continuous-time, discrete-state Markov chain, and the mixed time delays under consideration comprise both time-varying delays and continuously distributed...
This paper is concerned with the problem of robust exponential stability for discrete-time BAM neural networks with mode-dependent time delays and Markovian jump parameters, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, the global exponential stability is investigated. The time delay varies in an interval and depends on the mode of operation....
In this paper, we investigate the problem of global robust exponential stability for a class of cellular neural networks with mode-dependent time-varying delays and Markovian jump parameters by employing an improved free-weighting matrix approach. A new Markov process as discrete-time, discrete-state Markov process are considered. A mode-dependent time delays stability performance analysis result...
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