【摘要】 分析了区间变时滞的随机神经网络的全局渐进稳定性。区间变时滞不仅考虑了时变因素,而且考虑了时滞时变的上界和下界。通过Itö’s微分公式和构造适当的李雅普罗夫泛函,并且引入自由权值矩阵,以线性矩阵不等式形式给出了该系统在均方意义下的全局渐进稳定的充分性判据。数值算例进一步证明了结论的有效性。更多还原

【Abstract】 By Itö’s differential formula and combining the method of inequality analysis,the problem of stochastic asymptotical stability of a class of stochastic neural networks with time-varying delays and parameter uncertainties is investigated.The time-delay factors are unknown and time-varying with known bounds.Based on Lyapunov-Krasovskii functional and stochastic analysis approaches,some new stability criteria are presented in terms of linear matrix inequalities(LMIs)to guarantee the delayed neural network to be asymptotically stochastically asymptotically stable in the mean square for all admissible uncertainties.Numerical examples are given to demonstrate the usefulness of the proposed asymptotical stability criteria.更多还原