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On Stochastic Analysis Approaches for Comparing Complex Systems

机译:比较复杂系统的随机分析方法

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We compare two probabilistic approaches that have been proposed for the study and comparison of data obtained from experiment or simulations of a dynamical systems model. Both the approaches aim to carry out spectral analysis using a time-series data that is generated by a dynamical system. The first approach is based on constructing the so-called harmonic averages from the time-series data [1] and the second is an approach based on construction of a Markov chain from the data [2]. Results of the comparison using time-series data from a combustion model is provided.
机译:我们比较了两种用于研究和比较从动力学系统模型的实验或仿真获得的数据的概率方法。两种方法都旨在使用由动态系统生成的时间序列数据进行频谱分析。第一种方法是根据时间序列数据[1]构建所谓的谐波平均值,第二种方法是基于数据[2]构建马尔可夫链。提供了使用来自燃烧模型的时间序列数据的比较结果。

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