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Motif Extraction Algorithm of Time Series Based on DTW

Author: MaBaiMing
Tutor: FengLin
School: Dalian University of Technology
Course: Applied Computer Technology
Keywords: Time Series Dynamic Time Average method The middle of the sequence Keynote mode
CLC: O211.61
Type: Master's thesis
Year: 2011
Downloads: 20
Quote: 0
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Abstract


The time sequence is widely existence of an important type of data in the areas of finance , biology , science experiments . Classification, applications such as pattern extraction and anomaly detection , it is often the need to calculate the center of the collection of time sequence ( core sequence ) is used to represent the common mode . In some centers clustering method also must calculate the center of the time series , for example , k-means algorithm . Dynamic Time Warping (DTW) distance measure for time series has a strong advantage than the Euclidean distance . How to define based the DTW metric center sequence is a problem . Some of the literature in this regard , the attempt to define the center sequence , and given the central sequence solving method . In this paper, the definition of a new center sequence . The advantage of this definition is that the sequence to be able to make the center distance and the minimum of the other sequences , and thus more representative . This paper discusses the definition of this central sequence method for solving global constraints and local constraints . For the particularity of local constraints , the article focuses on the slope of the constraints of the solution , and gives an effective pruning algorithm . Center of two time series - based solution method , the paper gives the Methods Solving multiple sequence Center . The method uses aliquot collection , the shape of the first and other rules , to avoid the conventional simple pairwise method for solving the weaknesses. Finally , a large number of experiments to prove the rationality and superiority of this definition , the validity of the slope constraints pruning algorithm , as well as multi- center algorithm superiority sequences .

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CLC: > Mathematical sciences and chemical > Mathematics > Probability Theory and Mathematical Statistics > Theory of probability ( probability theory, probability theory ) > Random process > Smooth process and the process of second-order moment
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