H infinity state estimation for neutral-type neural networks with continuously distributed delays

This paper presents a model of neutral-type neural networks with continuously distributed delays. An H infinity state estimation problem is also proposed and formulated as a state estimator design problem. To solve the problem, the linear matrix inequality (LMI) method is considered in this paper. By constructing a Lyapunov-Krasovskii function (LKF), a sufficient condition for the existence of state estimator can be obtained. The desired estimator matrix gain can be characterized in terms of the solution to an LMI. One example is given to demonstrate the effectiveness of the proposed approach.