Global exponential stability of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays. (September 2016)

• Record Type: Journal Article
• Authors: Song, Qiankun; Yan, Huan; Zhao, Zhenjiang; Liu, Yurong
• Is Part Of: Neural networks. Volume 81(2016)
• Page Start: 1
• Page End: 10
• Publication Date: 2016-09
• Subjects: Complex-valued neural networks -- Stability -- Impulsive effects -- Asynchronous time-varying delays -- Distributed delays; Neural computers -- Periodicals; Neural networks (Computer science) -- Periodicals; Neural networks (Neurobiology) -- Periodicals; Nervous System -- Periodicals; Ordinateurs neuronaux -- Périodiques; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux neuronaux (Neurobiologie) -- Périodiques; Neural computers; Neural networks (Computer science); Neural networks (Neurobiology); Periodicals; 006.32
• DOI: 10.1016/j.neunet.2016.04.012
• Languages: English
• ISSNs: 0893-6080

Abstract

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.