Finite-Time Synchronization of Neural Networks with Interval and Distributed Time-Varying Delays via Feedback Control

Abstract

This research presents the problem of the finite-time synchronization of neural networks with interval and distributed time-varying delays. A state feedback control is planned for finite-time synchronization of neural networks. By constructing the Lyapunov-Krasovskii functional (LKF) is derived for finite-time stability criteria of neural network systems with interval and continuous differentiable time-varying delays. An extended reciprocally convex matrix inequality, a free-matrix-based integral inequality, Jensen's inequality and Wirtinger-based integral inequality are used to estimate the upper bound of the derivative of the LKF. The new sufficient finite-time stability conditions have been proposed in the form of linear matrix inequalities. Finally, a numerical example is presented to show the effectiveness of the proposed methods.