摘要：The problem of an H ∞ $H_{\infty}$ state estimation for discrete-time neural networks with time-varying and distributed delays is investigated in this paper. By constructing a new Lyapunov-Krasovskii functional and utilizing a reciprocally convex method, several sufficient conditions are derived in terms of linear matrix inequalities (LMIs). The results obtained in this paper are less conservative than the existing ones, which can be checked efficiently by using some standard numerical packages. Finally, three numerical examples are given to show the effectiveness of the proposed method.
关键词：state estimation ; discrete-time neural networks ; linear matrix inequalities (LMIs) ; time-varying and distributed delays
