首页> 外文会议>International Conference on Soft Computing and Intelligent Systems;International Symposium on Advanced Intelligent Systems >Relationship between logistic chaos and randomness using a matrix of probabilities and its application to the classification of time series: The line from chaos point to the reversed type of chaos is perpendicular to that from randomness's point to its reversed type
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Relationship between logistic chaos and randomness using a matrix of probabilities and its application to the classification of time series: The line from chaos point to the reversed type of chaos is perpendicular to that from randomness's point to its reversed type

机译:使用概率矩阵与随机性之间的关系及其在时间序列分类中的关系:来自混沌点到反向混沌的线垂直于从随机性点到其逆转类型的垂直于此

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Chaos theory has been applied to analyze the dynamics of time series in many fields. Some primary questions that are addressed are "What distinguished chaos from randomness?" or "What is the relationship between chaos and randomness". In this paper, by converting the time series of {X} to the series of signs of {Δx} such that Δx = x - x, logistic chaos can be represented by a probability matrix. Applying the probability matrices of the logistic chaos and randomness gives the following geometric property: The line from the point of chaos characterized type is perpendicular to the line from the point of randomness to that of the reversed type. Although the probability matrix is a necessary condition of time series, it can be applied to introduce distances from the time series of data to the quasi-chaos or the quasi-randomness and to propose a classification method for time series.
机译:混沌理论已被应用于分析许多领域时间序列的动态。 一些所解决的主要问题是“从随机性的混乱是什么区分?” 或者“混乱与随机性之间的关系是什么”。 在本文中,通过将{x}的时间序列转换为{Δx}的系列符号,使得Δx= x-x,逻辑混沌可以由概率矩阵表示。 应用逻辑混沌和随机性的概率矩阵给出了以下几何属性:来自混沌点的线路表征类型垂直于从随机性点到反向类型的线。 虽然概率矩阵是时间序列的必要条件,但是可以应用于从数据序列的距离引入准混乱或准随机性,并提出时间序列的分类方法。

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