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Delay-dependent stochastic stability criteria for Markovian jumping neural networks with mode-dependent time-varying delays and partially known transition rates |
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| Authors: | Junkang Tian Yongming LiJinzhou Zhao Shouming Zhong |
| Institution: | a State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, Sichuan 610500, PR China b School of Sciences, Southwest Petroleum University, Chengdu, Sichuan 610500, PR China c School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China |
| Abstract: | In this paper, the problem of stochastic stability criterion of Markovian jumping neural networks with mode-dependent time-varying delays and partially known transition rates is considered. Some new delay-dependent stability criteria are derived by choosing a new class of Lyapunov functional. The obtained criteria are less conservative because free-weighting matrices method and a convex optimization approach are considered. Finally, a numerical example is given to illustrate the effectiveness of the proposed method. |
| Keywords: | Stochastic stability Markovian jumping neural networks Time-varying delays |
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