Design of H∞ performance state estimator for static neural networks with time-varying delay

Abstract

In this paper, an improved integral inequality is proposed to design H∞ performance state estimator for delayed static neural networks (SNNs). A less conservative design criterion of H∞ performance state estimator is proposed, which ensures the asymptotic stability of estimation error system. Then, the criterion is applied to present a method for designing suitable estimator gain matrices and optimal H∞ performance index. A numerical example with simulation results is provided to verify the effectiveness of the proposed method.