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Stability of stochastic neural networks with Markovian jumping parameters

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3 Author(s)
Mingang, Hua ; Coll. of Automation Science and Engineering, South China Univ. of Technology, Guangzhou 510640, P. R. China ; Feiqi, Deng ; Yunjian, Peng

The global asymptotical stability for a class of stochastic delayed neural networks (SDNNs) with Markovian jumping parameters is considered. By applying Lyapunov functional method and Ito's differential rule, new delay-dependent stability conditions are derived. All results are expressed in terms of linear matrix inequality (LMI), and a numerical example is presented to illustrate the correctness and less conservativeness of the proposed method.

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Systems Engineering and Electronics, Journal of  (Volume:20 ,  Issue: 3 )