Overview

In recent years there has been an explosion of interest in wavelets, in a wide range of fields in science and engineering and beyond. This book brings together contributions from researchers from disparate fields, both in order to demonstrate to a wide readership the current breadth of work in wavelets, and to encourage cross-fertilization of ideas. It demonstrates the genuinely interdisplinary nature of wavelet research and applications. Particular areas covered include turbulence, statistics, time series analysis, signal and image processing, the physiology of vision, astronomy, economics and acoustics. Some of the work uses standard wavelet approaches and in other cases new methodology is developed. The papers were originally presented at a Royal Society Discussion Meeting, to a large and enthusiastic audience of specialists and non-specialists.

Full Product Details

Author:   B. W. Silverman (School of Mathematics, School of Mathematics, University of Bristol) ,  J. C. Vassilicos (Department of Applied Mathematics and Theoretical Physics, Department of Applied Mathematics and Theoretical Physics, University of Cambridge)
Publisher:   Oxford University Press
Imprint:   Oxford University Press
Dimensions:   Width: 16.30cm , Height: 2.00cm , Length: 24.00cm
Weight:   0.609kg
ISBN:  

9780198507161

ISBN 10:   019850716
Pages:   272
Publication Date:   15 June 2000
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   To order  
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Table of Contents

Daubechies, Guskov, Schroder, & Sweldens: Wavelets on irregular point sets Arneodo, Manneville, Muzy, & Roux: Revealing a lognormal cascading process in turbulent velocity statistics with wavelet analysis Nicolleau & Vassilicos: Wavelets for the study of intermittency and its topology Silverman: Wavelets in statistics: beyond the standard assumptions Johnstone: Wavelets and the theory of non-parametric function-estimation Candes & Donoho: Ridgelets: a key to higher-dimensional intermittency? Nason & Sachs: Wavelets in time-series analysis Field: Wavelets, vision, and the statistics of natural scenes Kingsbury: Image processing with complex wavelets Pen: Application of wavelets to filtering of noisy data Prandoni & Vetterli: Approximation and compression of piecewise smooth functions Ramsey: The contribution of wavelets to the analysis of economic and financial data Newland: Harmonic wavelets in vibrations and acoustics

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