H_∞ Filtering of Markovian Jumping Neural Networks with Time Delays

摘要

This paper focuses on studying the filtering problem of Markovian jumping neural networks with time delays. Based on a stochastic Lyapunov functional, a delay-dependent design criterion is presented under which the resulting filtering error system is stochastically stable and a prescribed H_∞ performance is guaranteed. It is shown that the gain matrices of the desired filter and the optimal performance index are simultaneously obtained by handing a convex optimization problem subject to some coupled linear matrix inequalities, which can be efficiently solved by some standard algorithms.