title: Robust exponential stability of markovian jumping neural networks with time-varying delay.
abstract: This paper considers the robust stability of a class of neural networks with Markovian jumping parameters and time-varying delay. By employing a new Lyapunov-Krasovskii functional, a sufficient condition for the global exponential stability of the delayed Markovian jumping neural networks is established. The proposed condition is also extended to the uncertain cases, which are shown to be the improvement and extension of the existing ones. Finally, the validity of the results are illustrated by an example.
authors.affiliation: College of Communication and Control Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, P. R. China. gaoyuming0820@yahoo.com.cn
authors.forename: Ming
authors.initials: M
authors.lastname: Gao
authors.forename: Xuyang
authors.initials: X
authors.lastname: Lou
authors.forename: Baotong
authors.initials: B
authors.lastname: Cui
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008390:Markov Chains; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D013997:Time Factors