Summary: | 碩士 === 國立臺北大學 === 統計學系 === 99 === In the recent years, multiscale entropy (MSE) has been widely adopted for engineering or medical researches and for analysis on the complexity of things researchers interest in, which all bringing in excellent research results. Therefore, the main purpose of this research is to use Sample entropy (SampEn) to calculate the complexity of fluctuations of time series. We use multiscale entropy at different time scales to explore the curve change of sequence data volatility. By observing and researching considerable amount of computer simulation data, we find out the way to use multiscale entropy to evaluate the possible time of structural changes of time series. Through this approach, the original sequence will be separated into several subsequences in case the data of subsequences is not enough. If the multiscale entropy curves among the sequences fluctuate in the same way, it means these sequences do not have structural changes. On the contrary, if one curve fluctuation from one subsequence is different from other subsequences’, this should mean this sequence has structural change and the change point may exist within it. These curve changes of the multiscale entropy and other different subsequences will be divided into several more subsequences; then we search over and over until we find the structural change point within the small interval.
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