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Stability of stochastic genetic networks with both Markovian jumping parameters and mixed time delays

机译:随机遗传网络与马尔可夫跳跃参数的稳定性和混合时间延迟

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This paper investigates the issue of stability for stochastic genetic networks with both Markovian jumping parameters and mixed time delays. The jumping parameters are modelled as a continuous-time discrete-state Markovian chain. By constructing Lyapunov functional and using linear matrix inequality (LMI) techniques, sufficient conditions for genetic regulatory networks to be asymptotically stable in the mean square are derived. Two numerical examples are given to illustrate the effectiveness of our results.
机译:本文调查了随机跳跃参数和混合时间延迟的随机遗传网络稳定性问题。 跳跃参数被建模为连续时间离散状态马尔可维亚链。 通过构建Lyapunov功能和使用线性矩阵不等式(LMI)技术,推导出遗传调节网络在平均方形中渐近稳定的足够条件。 给出了两个数值例子来说明我们的结果的有效性。

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