title: Global exponential stability of neural networks with time-varying delay based on free-matrix-based integral inequality.
abstract: This paper is concerned with global exponential stability problem for a class of neural networks with time-varying delays. Using a new proposed inequality called free-matrix-based integral inequality, a less conservative criterion is proposed, which is expressed by linear matrix inequalities. Two numerical examples are given to show the effectiveness and superiority of the obtained criterion.
authors.affiliation: School of Automation, China University of Geosciences, Wuhan 430074, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: He
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha, 410083, China.
authors.forename: Meng-Di
authors.initials: MD
authors.lastname: Ji
authors.affiliation: School of Automation, China University of Geosciences, Wuhan 430074, China; Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 3GJ, UK. Electronic address: ckzhang@cug.edu.cn.
authors.forename: Chuan-Ke
authors.initials: CK
authors.lastname: Zhang
authors.affiliation: School of Automation, China University of Geosciences, Wuhan 430074, China.
authors.forename: Min
authors.initials: M
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D016571:Neural Networks, Computer
keywords: Exponential stability; Lyapunov–Krasovskii functional; Neural networks; Time-varying delay