State estimation for discrete-time neural networks with time-varying delay

摘要: This article deals with the problem of delay-dependent state estimation for discrete-time neural networks time-varying delay. Our objective is to design a estimator neuron states through available output measurements such that error system guaranteed be globally exponentially stable. Based on linear matrix inequality approach, condition developed existence desired via novel Lyapunov functional. The obtained has less conservativeness than existing ones, which demonstrated by numerical example.