Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
408659 | Neurocomputing | 2010 | 9 Pages |
Abstract
This paper investigates the problem of stability analysis for a class of discrete-time stochastic neural networks (DSNNs) with time-varying delays. In the concerned model, stochastic disturbances are described by a Brownian motion, and time-varying delay d(k)d(k) satisfies dm≤d(k)≤dMdm≤d(k)≤dM. Based on the delay partitioning idea and some inequalities, a new stability criterion with less conservatism in terms of linear matrix inequalities (LMIs) is proposed by introducing a novel Lyapunov–Krasovskii functional combined with a free-weighting matrix method. The condition can be checked by utilizing some numerical software and a numerical example is provided to show the usefulness of the proposed condition.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yan Ou, Hongyang Liu, Yulin Si, Zhiguang Feng,