Title A new approach for optimal offline time-series segmentation with error bound guarantee
Authors Carmona-Poyato Á. , Fernández-Garcia N.L. , Madrid-Cuevas F.J. , DURAN ROSAL, ANTONIO MANUEL
External publication No
Means Pattern Recognit.
Scope Article
Nature Científica
JCR Quartile 1
SJR Quartile 1
Area International
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101905482&doi=10.1016%2fj.patcog.2021.107917&partnerID=40&md5=999eff462cff5235e6d69ec3a9114c08
Publication date 01/01/2021
ISI 000639744500001
Scopus Id 2-s2.0-85101905482
DOI 10.1016/j.patcog.2021.107917
Abstract Piecewise Linear Approximation is one of the most commonly used strategies to represent time series effectively and approximately. This approximation divides the time series into non-overlapping segments and approximates each segment with a straight line. Many suboptimal methods were proposed for this purpose. This paper proposes a new optimal approach, called OSFS, based on feasible space (FS) Liu et al. (2008)[1], that minimizes the number of segments of the approximation and guarantees the error bound using the L8-norm. On the other hand, a new performance measure combined with the OSFS method has been used to evaluate the performance of some suboptimal methods and that of the optimal method that minimizes the holistic approximation error (L2-norm). The results have shown that the OSFS method is optimal and demonstrates the advantages of L8-norm over L2-norm. © 2021 Elsevier Ltd
Keywords Piecewise linear techniques; Time series; Approximation errors; New approaches; Optimal approaches; Optimal methods; Performance measure; Piecewise linear approximations; Sub-optimal method; Time-seri
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