Wavelets: the Key to Intermittent Information? by B. W. SilvermanWavelets: the Key to Intermittent Information? by B. W. Silverman

Wavelets: the Key to Intermittent Information?

EditorB. W. Silverman, J. C. Vassilicos

Hardcover | July 17, 2000

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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 workin 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.
B. W. Silverman is in the School of Mathematics at University of Bristol. J. C. Vassilicos is in the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge.
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Title:Wavelets: the Key to Intermittent Information?Format:HardcoverPublished:July 17, 2000Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:019850716X

ISBN - 13:9780198507161

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Table of Contents

Daubechies, Guskov, Schroder, and Sweldens: Wavelets on irregular point setsArneodo, Manneville, Muzy, and Roux: Revealing a lognormal cascading process in turbulent velocity statistics with wavelet analysisNicolleau and Vassilicos: Wavelets for the study of intermittency and its topologySilverman: Wavelets in statistics: beyond the standard assumptionsJohnstone: Wavelets and the theory of non-parametric function-estimationCandes and Donoho: Ridgelets: a key to higher-dimensional intermittency?Nason and Sachs: Wavelets in time-series analysisField: Wavelets, vision, and the statistics of natural scenesKingsbury: Image processing with complex waveletsPen: Application of wavelets to filtering of noisy dataPrandoni and Vetterli: Approximation and compression of piecewise smooth functionsRamsey: The contribution of wavelets to the analysis of economic and financial dataNewland: Harmonic wavelets in vibrations and acoustics