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Using forbidden ordinal patterns to detect determinism in irregularly sampled time series

机译:使用禁止的顺序模式在不规则采样的时间序列中检测确定性

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摘要

It is known that when symbolizing a time series into ordinal patterns using the Bandt-Pompe (BP) methodology, there will be ordinal patterns called forbidden patterns that do not occur in a deterministic series. The existence of forbidden patterns can be used to identify deterministic dynamics. In this paper, the ability to use forbidden patterns to detect determinism in irregularly sampled time series is tested on data generated from a continuous model system. The study is done in three parts. First, the effects of sampling time on the number of forbidden patterns are studied on regularly sampled time series. The next two parts focus on two types of irregular-sampling, missing data and timing jitter. It is shown that forbidden patterns can be used to detect determinism in irregularly sampled time series for low degrees of sampling irregularity (as defined in the paper). In addition, comments are made about the appropriateness of using the BP methodology to symbolize irregularly sampled time series. (C) 2016 AIP Publishing LLC.
机译:众所周知,当使用Bandt-Pompe(BP)方法将时间序列符号化为序数模式时,将有确定性序列中不会出现的称为禁止模式的序数模式。禁止模式的存在可用于识别确定性动力学。在本文中,对从连续模型系统生成的数据测试了使用禁止模式检测不规则采样时间序列中确定性的能力。该研究分为三个部分。首先,在规则采样的时间序列上研究了采样时间对禁止模式数量的影响。接下来的两部分重点介绍两种类型的不规则采样:丢失数据和定时抖动。结果表明,对于低采样不规则度(如本文所定义),禁止模式可用于检测不规则采样时间序列中的确定性。此外,还对使用BP方法论来象征性地采样不定期的时间序列的适当性提出了意见。 (C)2016 AIP出版有限责任公司。

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