具有leakage时滞的随机马尔科夫跳变神经网络的稳定性

Stability of Discrete-Time Stochastic Neural Networks with Markovian Jumping and Time Delay in the Leakage Terms

研究一类具有leakage时滞的随机马尔科夫跳变神经网络的稳定性，通过构造一个新的Lyapunov-Kra—sovskii泛函，并应用It6公式、随机不等式技术，得到了基于线性矩阵不等式（LMI）的均方意义下的全局稳定性判定条件．

In this paper,a class of discrete-time stochastic neural networks with Markovian jump- ing and time delay in the leakage terms is investigated. By using the Lyapunov-Krasovskii func- tional and linear matrix inequality（LMI）approach, sufficient conditions are derived to ensure the global asymptotic stability in mean square for an equilibrium point of the neural networks.