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Stationary distribution of stochastic Markov jump coupled systems based on graph theory

机译:基于图论的随机马尔可夫跳跃耦合系统的固定分布

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This paper focuses on the existence of a stationary distribution of stochastic Markov jump coupled systems (SMJCSs) for the first time, in which the coupling effect is considered. A new technique that is combining the graph theory, M-matrix method with the Lyapunov method is used to study stationary distribution, and sufficient conditions are presented to ensure the existence of a stationary distribution, which are more applicable and suitable for various fields, such as neural networks, biomathematics, physics and so forth. Moreover, sufficient conditions presented indicate that the existing region of stationary distribution is related to stochastic disturbance and the dimension of a system closely. Also, theoretical results are applied to stochastic Markov jump coupled oscillators systems in physics and then a specific theorem is presented. Eventually, some simulations are given to verify the feasibility and availability of our theoretical results. (C) 2019 Elsevier Ltd. All rights reserved.
机译:本文首重侧重于第一次存在随机马尔可夫跳跃耦合系统(SMJCSS)的固定分布,其中考虑了耦合效果。一种结合图表理论的新技术,利用Lyapunov方法的M矩阵方法用于研究静止分布,并提出了充分的条件,以确保静止分布的存在,这更适用,适用于各个领域,这作为神经网络,生物疗法,物理等等。此外,提出的充分条件表明,现有的固定分布区域与紧紧的系统的随机扰动和维度相关。此外,理论结果应用于物理学中的随机马尔可夫跳跃耦合振荡器系统,然后呈现特定定理。最终,提供了一些模拟来验证我们理论结果的可行性和可用性。 (c)2019年elestvier有限公司保留所有权利。

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