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Wavelet Methods for Time SeriesAnalysis

Percival, Donald B., Walden, Andrew T.·2000·Cambridge University Press eBooks

Abstract

This introduction to wavelet analysis 'from the ground level and up', and to wavelet-based statistical analysis of time series focuses on practical discrete time techniques, with detailed descriptions of the theory and algorithms needed to understand and implement the discrete wavelet transforms. Numerous examples illustrate the techniques on actual time series. The many embedded exercises - with complete solutions provided in the Appendix - allow readers to use the book for self-guided study. Additional exercises can be used in a classroom setting. A Web site offers access to the time series and wavelets used in the book, as well as information on accessing software in S-Plus and other languages. Students and researchers wishing to use wavelet methods to analyze time series will find this book essential.

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Metadata

Authors
Percival, D. B., & Walden, A. T.
Venue
Cambridge University Press eBooks
Published
2000
OpenAlex
W4298352105
Cited by
3,065
References
0
FWCI
10.04
Type
book
Language
en
Open access
closed

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CoChat. (2026). Citation check: Wavelet Methods for Time SeriesAnalysis. https://app.cochat.ai/papers/10.1017/cbo9780511841040
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Percival, D. B., & Walden, A. T. (2000). Wavelet Methods for Time SeriesAnalysis. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511841040

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.