A New Time Series Similarity Measurement Method Based on the Morphological Pattern and Symbolic Aggregate Approximation

A New Time Series Similarity Measurement Method Based on the Morphological Pattern and Symbolic Aggregate Approximation

Aiming at the problem that the traditional similarity measurement methods cannot effectively measure the similarity of the time series with the difference both in the trend and detail, this paper proposes a new time series similarity measurement method (MP-SAX) based on the morphological pattern (MP...

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Bibliographic Details
Main Authors: Jiancheng Yin, Rixin Wang, Huailiang Zheng, Yuantao Yang, Yuqing Li, Minqiang Xu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Similarity measure
morphological pattern
symbolic aggregate approximation
longest common subsequence
empirical mode decomposition
Online Access:https://ieeexplore.ieee.org/document/8793127/

Internet

https://ieeexplore.ieee.org/document/8793127/

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