Finite-time H∞ state estimation for switched neural networks with time-varying delays

This study considers the problem of finite-time H∞H∞ state estimation for the switched neural networks with time varying delay, based on the theories of the switched systems. Sufficient conditions for the switched neural networks to be finite time stable and finite time bounded are derived. These conditions are delay dependent and are given in terms of linear matrix inequalities (LMIs). Average dwell time of switching signals is also given such that switched neural networks are finite-time stable or finite-time bounded. By resorting to the average dwell time approach and Lyapunov–Krasovskii functional technology, the H∞H∞ estimator design are developed in terms of solvability of a set of linear matrix inequalities. Finally, numerical examples are provided to illustrate the effectiveness of the theoretical results.