Exponential stability of impulsive stochastic recurrent neural networks with time-varying delays and Markovian jumping

In this paper, we consider a class of impulsive stochastic 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.