A Novel Similarity Measure Model for Multivariate Time Series Based on LMNN and DTW-Reference-Cited by-同舟云学术

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A Novel Similarity Measure Model for Multivariate Time Series Based on LMNN and DTW

Published:2016-09-26 Issue:3 Volume:45 Page:925-937
ISSN:1370-4621
Container-title:Neural Processing Letters
language:en
Short-container-title:Neural Process Lett

Author:

Shen Jingyi,Huang Weiping,Zhu Dongyang,Liang Jun

Funder

the National Natural Science Foundation of China

the Research Fund for the Doctoral Program of Higher Education in China

the Zhejiang Provincial Science and Technology Planning Projects of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Link

http://link.springer.com/article/10.1007/s11063-016-9555-5/fulltext.html

Reference29 articles.

1. Chan NH (2002) Time series: applications to finance. Wiley, Hoboken

2. Tormene P, Giorgino T, Quaglini S, Stefanelli M (2008) Matching incomplete time series with dynamic time warping: an algorithm and an application to post-stroke rehabilitation. Artif Intell Med 45(1):11–34

3. Seborg DE, Singhal A (2005) Clustering multivariate time-series data. J Chemom 19(8):427–438

4. Aach J, Church GM (2001) Aligning gene expression time series with time warping algorithms. Bioinformatics 17(6):495–508

5. Cover TM, Hart PE (1967) Nearest neighbor pattern classification. IEEE Trans Inf Theory 13(1):21–27

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