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Interaction Detection via Probabilistic Fuzzy Logic for Coupled Dynamical Systems

机译:耦合动力系统中基于概率模糊逻辑的交互检测

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Interaction detection for coupled dynamical systems plays a key role in understanding natural complex systems, and it is a difficult problem to establish the presence of coupling and interaction in the case of nonlinearity and noise. In this paper, a novel interaction detection algorithm has been proposed based on the probabilistic fuzzy logic by testing the degree of changes of one dynamical system caused by the other dynamical system with the observation time series of these two systems. The simulation results on the weekly coupled Henon maps show that the proposed algorithm with higher order of Markov property becomes more robust as noise increase in the observation data.
机译:耦合动力系统的相互作用检测在理解自然复杂系统中起着关键作用,在非线性和噪声的情况下,建立耦合和相互作用的存在是一个困难的问题。本文提出了一种基于概率模糊逻辑的交互检测算法,该算法通过观测一个系统的观测时间序列,来测试一个系统动态变化对另一系统动态变化的影响程度。在每周耦合的Henon映射上的仿真结果表明,随着观测数据中噪声的增加,所提出的具有较高马尔可夫性质的算法变得更加健壮。

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