Discrete Wavelet Transform-Based Time Series Analysis and Mining

作者：Chaovalit Pimwadee^*; Gangopadhyay Aryya; Karabatis George; Chen Zhiyuan

来源：ACM Computing Surveys, 2011, 43(2): 6.

DOI：10.1145/1883612.1883613

• Algorithms
• Experimentation
• Measurement
• Performance
• Classification
• clustering
• anomaly detection
• similarity search
• prediction
• data transformation
• dimensionality reduction
• noise filtering
• data compression

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.

• 出版日期2011-1