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A simple way of distinguishing chaotic characteristics in ECG signals

机译:区分ECG信号中混沌特性的简单方法

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Accurate identification of chaotic behavior from a deterministic periodic process is a difficult but significant issue as underlying dynamics in the data determines the sequent analysis techniques. Since both chaotic and periodic time series can have the similar waveform and spectrum the commonly used approaches for detecting chaotic behavior have limitation. So in this paper, we present an alternative method to observe the prediction on the trajectories of the given system against variable prediction time lags by using the nonparametric model. While applying the method to numerical data and three types of electrocardiogram (ECG) data, the results demonstrate that the approach we adopted can reveal the distinction between the chaos and periodic process, and is a convenient and effective tool for practical application
机译:从确定性的周期性过程中准确识别混沌行为是一个困难但重要的问题,因为数据中的基本动态决定了后续的分析技术。由于混沌和周期性时间序列都可以具有相似的波形和频谱,因此用于检测混沌行为的常用方法具有局限性。因此,在本文中,我们提出了一种使用非参数模型来观察针对给定系统的轨迹的预测的方法,该方法针对可变的预测时间滞后。在将该方法应用于数值数据和三种心电图数据时,结果表明我们采用的方法可以揭示混沌与周期性过程之间的区别,是一种方便有效的实用工具

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