Less conservative results of state estimation for neural networks with time-varying delay

In this paper, the state estimation problem is investigated for continuous-time neural networks with time-varying delay through available output measurements. By constructing more effective Lyapunov functionals, and combining with Jensen integral inequality or free-weighting matrix approach, several less conservative sufficient conditions for the existence of state estimator are derived in terms of linear matrix inequalities (LMIs). Finally, a numerical example is presented to demonstrate the effectiveness and the reduced conservatism of proposed results.