Free-weighting-matrix inequality for exponential stability for neural networks with time-varying delay

Exponential stability for neural networks with time-varying delay is considered in this paper. By extend-ing the generalized free-weighting-matrix integral inequality, a novel integral inequality is derived by using weighted orthogonal functions. Then the new inequality is applied to investigate the exponential stability of time delay neural networks via an improved Lyapunov-Krasovskii functional. Numerical examples are given to verify the advantages of the proposed criterion. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper discusses the exponential stability of neural networks with time-varying delay. A novel integral inequality is derived by extending the generalized free-weighting-matrix integral inequality and using weighted orthogonal functions. The new inequality is then applied to investigate the exponential stability of time delay neural networks via an improved Lyapunov-Krasovskii functional, with numerical examples provided to demonstrate the advantages of the proposed criterion.