title: Passivity analysis for discrete-time stochastic Markovian jump neural networks with mixed time delays.
abstract: In this paper, passivity analysis is conducted for discrete-time stochastic neural networks with both Markovian jumping parameters and mixed time delays. The mixed time delays consist of both discrete and distributed delays. The Markov chain in the underlying neural networks is finite piecewise homogeneous. By introducing a Lyapunov functional that accounts for the mixed time delays, a delay-dependent passivity condition is derived in terms of the linear matrix inequality approach. The case of Markov chain with partially unknown transition probabilities is also considered. All the results presented depend upon not only discrete delay but also distributed delay. A numerical example is included to demonstrate the effectiveness of the proposed methods.
authors.affiliation: National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China. nashwzhg@gmail.com
authors.forename: Zheng-Guang
authors.initials: ZG
authors.lastname: Wu
authors.forename: Peng
authors.initials: P
authors.lastname: Shi
authors.forename: Hongye
authors.initials: H
authors.lastname: Su
authors.forename: Jian
authors.initials: J
authors.lastname: Chu
mesh_terms: D000465:Algorithms; D006801:Humans; D016014:Linear Models; D008390:Markov Chains; D016571:Neural Networks, Computer; D013269:Stochastic Processes; D013997:Time Factors