State Feedback Stabilization for Neutral-Type Neural Networks with Time-Varying Discrete and Unbounded Distributed Delays

Abstract EN

The problem of stabilization for a class of neutral-type neural networks with discrete and unbounded distributed delays is investigated.

By introducing an appropriate Lyapunov-Krasovskii functional and using Jensen inequality technique to deal with its derivative, delay-range-dependent and rate-dependent stabilization criteria are presented in the form of LMIs with nonlinear constraints.

In order to solve the nonlinear problem, a cone complementarity linearization (CCL) algorithm is offered.

In addition, several numerical examples are provided to illustrate the applicability of the proposed approach.