Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6863801 | Neurocomputing | 2018 | 17 Pages |
Abstract
This paper studies the problem of exponential synchronization for a class of Markovian jump complex dynamical networks (MJCDNs) with stochastic disturbances and partially uncertain transition. By constructing the novel stochastic Lyapunov-Krasovskii function (LKF), and utilizing stochastic analysis, feedback pinning control technique and inequality techniques, some sufficient criteria are established in terms of linear matrix inequalities (LMIs) to guarantee the exponential synchronization of the MJCDNs with time delays and without it. Finally, according to a Markovian chain with partially uncertain transition rates, some numerical examples are given to demonstrate the effectiveness of the proposed results.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yanan Wang, Yuechao Ma, Aihong Chen,