淡江大學機構典藏:Item 987654321/118912
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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/118912


    Title: Retrospective analysis for phase I statistical process control and process capability study using revised sample entropy
    Authors: Chang, Shing I.;Zhang, Zheng;Koppel, Siim;Malmir, Behnam;Kong, Xianguang;Tsai, Tzong-Ru;Wang, Donghai
    Keywords: Sample entropy;Change points;Process capability analysis;Statistical process control
    Date: 2018-06-13
    Issue Date: 2020-07-14 12:10:38 (UTC+8)
    Publisher: Springer U K
    Abstract: This study explored a new nonparametric analytical method for identifying heterogeneous segments in time-series data for data-abundant processes. A sample entropy (SampEn) algorithm often used in signal processing and information theory can also be used in a time series or a signal stream, but the original SampEn is only capable of quantifying process variation changes. The proposed algorithm, the adjusted sample entropy (AdSEn), is capable of identifying process mean shifts, variance changes, or mixture of both. A simulation study showed that the proposed method is capable of identifying heterogeneous segments in a time series. Once segments of change points are identified, any existing change-point algorithms can be used to precisely identify exact locations of potential change points. The proposed method is especially applicable for long time series with many change points. Properties of the proposed AdSEn are provided to demonstrate the algorithm’s multi-scale capability. A table of critical values is also provided to help users accurately interpret entropy results.
    Relation: Neural Computing and Applications 31, p.7415-7428
    DOI: 10.1007/s00521-018-3556-4
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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