Exponential Stability of Impulsive Stochastic Recurrent Neural Networks with Time-Varying Delays and Markovian Jumping

Exponential Stability of Impulsive Stochastic Recurrent Neural Networks with Time-Varying Delays and Markovian Jumping

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摘要 In this paper, we consider a class of impulsive stochas- tic recurrent neural networks with time-varying delays and Markovian jumping. Based on some impulsive delay differential inequalities, some easy-to-test conditions such that the dynamics of the neural network is stochastically exponentially stable in the mean square, independent of the time delay, are obtained. An example is also given to illustrate the effectiveness of our results. In this paper, we consider a class of impulsive stochas- tic recurrent neural networks with time-varying delays and Markovian jumping. Based on some impulsive delay differential inequalities, some easy-to-test conditions such that the dynamics of the neural network is stochastically exponentially stable in the mean square, independent of the time delay, are obtained. An example is also given to illustrate the effectiveness of our results.

作者 XU Congcong

机构地区 Institute of Information Technology

出处《Wuhan University Journal of Natural Sciences》 CAS 2014年第1期71-78,共8页 武汉大学学报（自然科学英文版）

关键词 exponential stability stochastic recurrent neural network Markovian jumping IMPULSIVE time-varying delays exponential stability stochastic recurrent neural network Markovian jumping impulsive time-varying delays

分类号 TP183 [自动化与计算机技术—控制理论与控制工程]

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Wuhan University Journal of Natural Sciences

2014年第1期

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Exponential Stability of Impulsive Stochastic Recurrent Neural Networks with Time-Varying Delays and Markovian Jumping

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