title: Novel conditions on exponential stability of a class of delayed neural networks with state-dependent switching.
abstract: This paper is concerned with the global exponential stability on a class of delayed neural networks with state-dependent switching. Under the novel conditions, some sufficient criteria ensuring exponential stability of the proposed system are obtained. In particular, the obtained conditions complement and improve earlier publications on conventional neural networks with continuous or discontinuous right-hand side. Numerical simulations are also presented to illustrate the effectiveness of the obtained results.
authors: College of Mathematics and statistics, South-Central University For Nationalities, Wuhan 430074, China. Electronic address: zgdhbnu@163.com.
authors: Guodong
authors: G
authors: Zhang
authors: School of Automation, Huazhong University of Science and Technology, Wuhan, 430074, China.
authors: Yi
authors: Y
authors: Shen
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016571:Neural Networks, Computer; D013569:Synapses
keywords: Exponential stability; Filippov solutions; Switching neural networks; Time-varying delays