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Wavelet Methods for Time Series Analysis Donald B. Percival (University of Washington)

Wavelet Methods for Time Series Analysis By Donald B. Percival (University of Washington)

Wavelet Methods for Time Series Analysis by Donald B. Percival (University of Washington)


Summary

This introduction to wavelet analysis and 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. The book contains numerous exercises and a website offering access to the time series and wavelet software.

Wavelet Methods for Time Series Analysis Summary

Wavelet Methods for Time Series Analysis by Donald B. Percival (University of Washington)

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.

Wavelet Methods for Time Series Analysis Reviews

'In my opinion the book by Percival and Walden should be available in every university library, and every time-series analyst must read this book for an alternative (to Fourier) set of techniques.' T. Subba Rao, Publication of the International Statistical Institute
'... would be an ideal text for a statistics doctoral student who is new to the field of wavelets ... the content, lay-out and consistency of the text mean that it should also be a valuable reference resource for the wavelet researcher.' Tim Downie, The Statistician
'The authors ... provide considerable background material, tell their story from scratch, proceed at a careful pace ... and work out detailed applications ... Recommended.' Choice

Table of Contents

1. Introduction to wavelets; 2. Review of Fourier theory and filters; 3. Orthonormal transforms of time series; 4. The discrete wavelet transform; 5. The maximal overlap discrete wavelet transform; 6. The discrete wavelet packet transform; 7. Random variables and stochastic processes; 8. The wavelet variance; 9. Analysis and synthesis of long memory processes; 10. Wavelet-based signal estimation; 11. Wavelet analysis of finite energy signals; Appendix. Answers to embedded exercises; References; Author index; Subject index.

Additional information

NLS9780521685085
9780521685085
0521685087
Wavelet Methods for Time Series Analysis by Donald B. Percival (University of Washington)
New
Paperback
Cambridge University Press
20060227
622
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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Customer Reviews - Wavelet Methods for Time Series Analysis