Delay-dependent stability analysis of neural networks with time-varying delay: A generalized free-weighting-matrix approach

Zhang, Chuan-Ke, He, Yong, Jiang, Lin ORCID: 0000-0001-6531-2791, Lin, Wen-Juan and Wu, Min (2017) Delay-dependent stability analysis of neural networks with time-varying delay: A generalized free-weighting-matrix approach. APPLIED MATHEMATICS AND COMPUTATION, 294. pp. 102-120.

Text final AMC-D-16-01489.pdf - Author Accepted Manuscript Download (283kB)

Abstract

This paper investigates the delay-dependent stability problem of continuous neural networks with a bounded time-varying delay via Lyapunov–Krasovskii functional (LKF) method. This paper focuses on reducing the conservatism of stability criteria by estimating the derivative of the LKF more accurately. Firstly, based on several zero-value equalities, a generalized free-weighting-matrix (GFWM) approach is developed for estimating the single integral term. It is also theoretically proved that the GFWM approach is less conservative than the existing methods commonly used for the same task. Then, the GFWM approach is applied to investigate the stability of delayed neural networks, and several stability criteria are derived. Finally, three numerical examples are given to verify the advantages of the proposed criteria.

Item Type:	Article
Uncontrolled Keywords:	Neural networks, Time-varying delay, Generalized free-weighting-matrix approach, Stability
Depositing User:	Symplectic Admin
Date Deposited:	15 Feb 2017 08:45
Last Modified:	19 Jan 2023 07:19
DOI:	10.1016/j.amc.2016.08.043
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3005810

Available Versions of this Item

• Delay-dependent stability analysis of neural networks with time-varying delay: A generalized free-weighting-matrix approach. (deposited 13 Feb 2017 10:44)
  • Delay-dependent stability analysis of neural networks with time-varying delay: A generalized free-weighting-matrix approach. (deposited 15 Feb 2017 08:45) [Currently Displayed]