Dissipativity Analysis for Neural Networks With Time-Varying Delays via a Delay-Product-Type Lyapunov Functional Approach

IEEE Trans Neural Netw Learn Syst. 2021 Mar;32(3):975-984. doi: 10.1109/TNNLS.2020.2979778. Epub 2021 Mar 1.

Abstract

This article is concerned with the problem of dissipativity and stability analysis for a class of neural networks (NNs) with time-varying delays. First, a new augmented Lyapunov-Krasovskii functional (LKF), including some delay-product-type terms, is proposed, in which the information on time-varying delay and system states is taken into full consideration. Second, by employing a generalized free-matrix-based inequality and its simplified version to estimate the derivative of the proposed LKF, some improved delay-dependent conditions are derived to ensure that the considered NNs are strictly ( Q , S , R )- γ -dissipative. Furthermore, the obtained results are applied to passivity and stability analysis of delayed NNs. Finally, two numerical examples and a real-world problem in the quadruple tank process are carried out to illustrate the effectiveness of the proposed method.

Publication types

  • Research Support, Non-U.S. Gov't