期刊
NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS
卷 13, 期 5, 页码 2259-2270出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.nonrwa.2012.01.021
关键词
Delayed recurrent neural network; Time varying delay; Impulse control; Linear matrix inequality; Exponential stability; Markovian jump parameter
资金
- National Natural Science Foundation of China [10801056, 11072059]
- Natural Science Foundation of Ningbo [2010A610094]
- Specialized Research Fund for the Doctoral Program of Higher Education [20110092110017]
This paper is concerned with the stability of delayed recurrent neural networks with impulse control and Markovian jump parameters. The jumping parameters are modeled as a continuous-time, discrete-state Markov process. By applying the Lyapunov stability theory, Dynkin's formula and linear matrix inequality technique, some new delay-dependent conditions are derived to guarantee the exponential stability of the equilibrium point. Moreover, three numerical examples and their simulations are given to show the less conservatism and effectiveness of the obtained results. In particular, the traditional assumptions on the differentiability of the time varying delays and the boundedness of their derivatives are removed since the time varying delays considered in this paper may not be differentiable, even not continuous. (C) 2012 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据