Estimator design for discrete-time switched neural networks with asynchronous switching and time-varying delay

This brief deals with the estimator design problem for discrete-time switched neural networks with time-varying delay. One main problem is the asynchronous-mode switching between the neuron state and the estimator. Our goal is to design a mode-dependent estimator for the switched neural networks under average dwell time switching such that the estimation error system is exponentially stable with a prescribed l₂ gain (in the H _∞ sense) from the noise signal to the estimation error. A new Lyapunov functional is constructed that may increase during the mismatched switchings. New results on the stability and l₂ gain analysis are then obtained. The admissible estimator gains are computed by solving a set of linear matrix inequalities. The relations among the switching law, the maximal delay upper bound, and the optimal H_∞ disturbance attenuation level are established. The effectiveness of the proposed design method is finally illustrated by a numerical example.