The state estimation for discrete-time delayed standard neural networks model

In this paper, the problem of state estimation for discrete-time delayed standard neural networks model (DDSNNM) is investigated. By constructing suitable Lyapunov-Krasovskii functional, the state-feedback controller is designed such that the close-loop error system is asymptotically stable. The existence condition of the state estimator was proposed in the form of linear matrix inequality, so the estimator gain matrix can be obtained easily by solving the LMI. The simulation is given to illustrate the effectiveness of our method.