Discrete Wavelet transform-based time series analysis and mining
Abstract
Time series are recorded values of an interesting phenomenon such as stock prices, household incomes, or patient heart rates over a period of time. Time series data mining focuses on discovering interesting patterns in such data. This article introduces a wavelet-based time series data analysis to interested readers. It provides a systematic survey of various analysis techniques that use discrete wavelet transformation (DWT) in time series data mining, and outlines the benefits of this approach demonstrated by previous studies performed on diverse application domains, including image classification, multimedia retrieval, and computer network anomaly detection.
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Analysis of time series data in the frequency domain enables extraction of unseen patterns and trends across data.
“Analysis of time series data in the frequency domain enables to extract unseen patterns and trends across data [87].”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [87]
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A cross-correlation technique in wavelet domain for detection of stochastic gravitational wavesPreprint
Klimenko, S., Mitselmakher, G., & Sazonov, A. (2002) · arXiv (Cornell University) · doi:10.48550/arxiv.gr-qc/0208007 · Cited by 11 · see citing works
A method for clustering transient data streams
Chaovalit, P., & Gangopadhyay, A. (2009) · ACM Symposium on Applied Computing · doi:10.1145/1529282.1529622 · Cited by 11 · see citing works
Self-citationCLASSIFICATION AND DETECTION OF ABNORMAL EVENTS IN TIME SERIES OF GRAPHS
Bunke, H., & Kraetzl, M. (2004) · Series in machine perception and artificial intelligence · doi:10.1142/9789812565402_0006 · Cited by 9 · see citing works
Efficient hemodynamic event detection utilizing relational databases and wavelet analysis
Saeed, M., & Mark, R. G. (2002) · Computers in cardiology · doi:10.1109/cic.2001.977614 · Cited by 7 · see citing works
An Efficient Recursive Partitioning Algorithm for Classification, Using Wavelets
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Medical decision support in clinical record management systems
Rizzi, S., & Sartoni, F. (2002) · doi:10.1109/icesd.1994.302269 · Cited by 3 · see citing works
Wang, Y., Wang, Y., & Spencer, P. (2006) · doi:10.1109/isbi.2006.1625086 · Cited by 3 · see citing works
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Banaee, H., Ahmed, M., & Loutfi, A. (2013) · Sensors · doi:10.3390/s131217472 · Cited by 452 · see citing works
- Authors
- Chaovalit, P., Gangopadhyay, A., Karabatis, G., & Chen, Z.
- Affiliations
- National Science and Technology Development Agency (TH)
- University of Maryland, Baltimore County (US)
- Venue
- ACM Computing Surveys
- Published
- 2011-01
- Volume
- 43
- Issue
- 2
- Pages
- 1-37
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W1971353559
- Cited by
- 218
- References
- 127
- Citations by year
- 2026: 15 · 2025: 23 · 2024: 17 · 2023: 24 · 2022: 15 · 2021: 20 · 2020: 17 · 2019: 13 · 2018: 17 · 2017: 10 · 2016: 9 · 2015: 10 · 2014: 11 · 2013: 7 · 2012: 9
- FWCI
- 12.85
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Computing Surveys (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Signal Processing › Time Series Analysis and Forecasting
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical Analysis and Transform Methods
- Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
- Keywords
- discrete wavelet transform, time series data mining, time series analysis, pattern discovery, image classification, multimedia retrieval, network anomaly detection
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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