Empirical study of symbolic aggregate approximation for time series classification-Reference-Cited by-同舟云学术

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Empirical study of symbolic aggregate approximation for time series classification

Published:2017-01-10 Issue:1 Volume:21 Page:135-150
ISSN:1088-467X
Container-title:Intelligent Data Analysis
language:
Short-container-title:IDA

Author:

Song Wei¹¹,Wang Zhiguang²¹,Zhang Fan³,Ye Yangdong¹,Fan Ming¹

Affiliation:

1. School of Information Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China

2. Deparment of Computer Science, University of Maryland, Baltimore County, MD 21250, USA

3. School of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, Henan, China

Publisher

IOS Press

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Theoretical Computer Science

Reference31 articles.

1. Grinsted A., Moore J.C. and Jevrejeva S., Application of the cross wavelet transform and wavelet coherence to geophysical time series, Nonlinear Processes in Geophysics 11(5/6) (2004), 561-566.

2. Climate signal detection using wavelet transform: How to make a time series sing;Lau;Bulletin of the American Meteorological Society,1995

3. Scaling behaviour of heartbeat intervals obtained by wavelet-based time-series analysis;Ivanov;Nature,1996

4. Efficiently supporting ad hoc queries in large datasets of time sequences;Korn;ACM SIGMOD Record,1997

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