Delay-dependent stability criteria for time-varying delay neural networks in the delta domain

In this paper, the delay-dependent stability criterion for time-varying delay neural networks in the delta domain is investigated. The unified neural networks, which can be used in both continues-time space and discrete-time space, takes advantage with a high sampling frequency. In the framework of the newly proposed neural networks, the delay-dependent stability criteria is derived in terms of linear matrix inequality by constructing the Lyapunov-Krasovskii function in the delta domain. A numerical simulation is given to show the effectiveness and superiority of the proposed approach.