Non-fragile state estimation for discrete-time complex networks with randomly occurring time-varying delays
Sunjie Zhang, Jingyang Mao, Derui Ding, Le Wei Yan · 2017
In this paper, the non-fragile state estimation problem is investigated for a class of discrete time-delay nonlinear complex networks with randomly occurring gain variations. Two sequences of random variables obeying the Bernoulli distribution are employed to describe the phenomena of randomly occurring time-varying delays and randomly occurring gain variations. Through stochastic analysis and Lyapunov functional approach, sufficient conditions are derived such that the addressed state estimation system ensures the exponential mean-square stability. Finally, a simulation example is provided to show the usefulness and effectiveness of the proposed state estimation conditions in this paper.