title: Global exponential stability of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays.
abstract: This paper investigates the stability problem for a class of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays. By employing the idea of vector Lyapunov function, M-matrix theory and inequality technique, several sufficient conditions are obtained to ensure the global exponential stability of equilibrium point. When the impulsive effects are not considered, several sufficient conditions are also given to guarantee the existence, uniqueness and global exponential stability of equilibrium point. Two examples are given to illustrate the effectiveness and lower level of conservatism of the proposed criteria in comparison with some existing results.
authors.affiliation: Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, China. Electronic address: qiankunsong@163.com.
authors.forename: Qiankun
authors.initials: Q
authors.lastname: Song
authors.affiliation: School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 400074, China. Electronic address: huanyancquc@163.com.
authors.forename: Huan
authors.initials: H
authors.lastname: Yan
authors.affiliation: Department of Mathematics, Huzhou Teachers College, Huzhou 313000, China. Electronic address: zhaozjcn@163.com.
authors.forename: Zhenjiang
authors.initials: Z
authors.lastname: Zhao
authors.affiliation: Department of Mathematics, Yangzhou University, Yangzhou 225002, China; Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia. Electronic address: liuyurong@gmail.com.
authors.forename: Yurong
authors.initials: Y
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D016571:Neural Networks, Computer; D013997:Time Factors
keywords: Asynchronous time-varying delays; Complex-valued neural networks; Distributed delays; Impulsive effects; Stability