Parameter-free Spikelet: Discovering Different Length and Warped Time Series Motifs using an Adaptive Time Series Representation

Author:

Imamura Makoto1ORCID,Nakamura Takaaki2ORCID

Affiliation:

1. Tokai University Educational System, Tokyo Minato-ku, Japan

2. Mitsubishi Electric Corporation, Kanagawa-ken Kamakura, Japan

Funder

JSPS KAKENHI Grant

Publisher

ACM

Reference25 articles.

1. Alee , S. , Mercer , R. Kamgar and Keogh, E. XXII: Matrix Profile Exact Discovery of Time Series Motifs under DTW , IEEE ICDM , pp. 900 -- 905 ( 2020 ). Alee, S., Mercer, R. Kamgar and Keogh, E. XXII: Matrix Profile Exact Discovery of Time Series Motifs under DTW, IEEE ICDM, pp. 900--905 (2020).

2. A survey of methods for time series change point detection

3. Probabilistic discovery of time series motifs

4. F. Fang and T. Shinozaki . Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems. PloS one, 13(2) ( 2018 ). F. Fang and T. Shinozaki. Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems. PloS one, 13(2) (2018).

5. Domain agnostic online semantic segmentation for multi-dimensional time series

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