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 conditi...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.展开更多
In this paper, an impulsive control strategy is proposed for a class of nonlinear stochastic dynamical networks with time-varying delay. Using the Lyapunov stability theory, a sufficient verifiable criterion for the e...In this paper, an impulsive control strategy is proposed for a class of nonlinear stochastic dynamical networks with time-varying delay. Using the Lyapunov stability theory, a sufficient verifiable criterion for the exponential synchronization is derived analytically. Finally, a numerical simulation example is provided to verify the effectiveness of the proposed approach.展开更多
文摘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.
文摘In this paper, an impulsive control strategy is proposed for a class of nonlinear stochastic dynamical networks with time-varying delay. Using the Lyapunov stability theory, a sufficient verifiable criterion for the exponential synchronization is derived analytically. Finally, a numerical simulation example is provided to verify the effectiveness of the proposed approach.