期刊
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
卷 7, 期 6, 页码 1005-1022出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s13042-014-0306-5
关键词
Robust stability; Genetic regulatory networks; Delay decomposing; Reciprocally convex combination; Lyapunov-Krasovskii functional
This study is concerned with the robust stability problem of uncertain genetic regulatory networks (GRNs) with random discrete time delays and distributed time delays which exist both in translation process and feedback regulation process. By utilizing a novel Lyapunov-Krasovskii functional which contains some triple integral terms and takes into account the ranges of delays, we derive sufficient delay-dependent conditions to ensure the asymptotically stability of GRNs with mixed time delays. Moreover, based on the idea of delay decomposing'', reciprocally convex combination approach'', less conservative conditions are obtained by using the lower bound lemma together with Jensen inequality. In addition, two corollaries are also been presented. Finally, numerical examples are presented to show the effectiveness of our proposed methods.
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