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Robust stability of genetic regulatory networks with interval time-varying delays under intrinsic and extrinsic noises

机译:具有内在和外在噪声下具有时变间隔时滞的遗传调节网络的鲁棒稳定性

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Gene regulation is inherently a stochastic process due to intrinsic and extrinsic noises which cause the fluctuations and uncertainties of kinetic parameters. On the other hand, time delays are usually inevitable due to different biochemical reactions in the genetic regulatory networks (GRNs) which are also affected by noises. Therefore, in this paper, we propose a GRN model that is subject to additive and multiplicative noises as well as time-varying delays. The time-varying delay is assumed to belong to an interval and no restriction on the derivative of the time-varying delay is needed, which allows the delay to be a fast time-varying function. Robust stochastic stability of such GRNs with disturbance attenuation is analyzed by applying the control theory and mathematical tools. Based on the Lyapunov method, new stability conditions are derived in the form of linear matrix inequalities (LMIs) that are dependent on the upper and lower bounds of time delays. An example is employed to illustrate the applicability and usefulness of the developed theoretical results.
机译:由于内在和外在的噪声会引起动力学参数的波动和不确定性,因此基因调控本质上是一个随机过程。另一方面,由于遗传调控网络(GRN)中不同的生化反应也常常会不可避免地造成时间延迟,这也受到噪声的影响。因此,在本文中,我们提出了一个GRN模型,该模型会受到加性和乘性噪声以及时变延迟的影响。假设时变延迟属于一个间隔,并且不需要对时变延迟的导数进行限制,这使得该延迟成为快速的时变函数。通过应用控制理论和数学工具,分析了具有扰动衰减的此类GRN的鲁棒随机稳定性。基于Lyapunov方法,以线性矩阵不等式(LMI)的形式导出新的稳定性条件,该线性矩阵不等式取决于时间延迟的上限和下限。通过一个例子来说明所发展的理论结果的适用性和实用性。

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