Lokenath Debnath

Wavelet Transforms and Their Applications (eBook, PDF)

• Format: PDF

Produktbeschreibung

Overview Historically, the concept of "ondelettes" or "wavelets" originated from the study of time-frequency signal analysis, wave propagation, and sampling theory. One of the main reasons for the discovery of wavelets and wavelet transforms is that the Fourier transform analysis does not contain the local information of signals. So the Fourier transform cannot be used for analyzing signals in a joint time and frequency domain. In 1982, Jean MorIet, in collaboration with a group of French engineers, first introduced the idea of wavelets as a family of functions constructed by using translation and dilation of a single function, called the mother wavelet, for the analysis of nonstationary signals. However, this new concept can be viewed as the synthesis of various ideas originating from different disciplines including mathematics (Calder6n-Zygmund operators and Littlewood-Paley theory), physics (coherent states in quantum mechanics and the renormalization group), and engineering (quadratic mirror filters, sideband coding in signal processing, and pyramidal algorithms in image processing). Wavelet analysis is an exciting new method for solving difficult problems in mathematics, physics, and engineering, with modern applications as diverse as wave propagation, data compression, image processing, pattern recognition, computer graphics, the detection of aircraft and submarines, and improvement in CAT scans and other medical image technology. Wavelets allow complex information such as music, speech, images, and patterns to be decomposed into elementary forms, called the fundamental building blocks, at different positions and scales and subsequently reconstructed with high precision.

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Produktdetails

• Verlag: Birkhäuser Boston
• Seitenzahl: 565
• Erscheinungstermin: 28. Juni 2011
• Englisch
• ISBN-13: 9781461200970
• Artikelnr.: 44194747

Autorenporträt

Lokenath Debnath, Ph.D., is a Professor of Mathematics at The University of Texas-Pan American. He received his Ph.D. in Applied Mathematics from the University of London, and a Ph.D. in Pure Mathematics from the University of Calcutta.  His areas of interest are applied mathematics, applied partial differential equations, integral transforms, fluid dynamics, and continuum mechanics. Firdous Ahmad Shah, Ph.D., is an Assistant Professor in the Post Graduate Department of Mathematics at the University of Kashmir.  His areas of specialization are: wavelets, wavelet packets, applications of wavelets in financial time series, and wavelet neural networks.

Inhaltsangabe

Brief Historical Introduction.- Hilbert Spaces and Orthonormal Systems.- Fourier Transformations and Their Applictions.- The Gabor Transform and Time-Frequency Signal Analysis.- The Wigner-Ville Distribution and Time-Frequency Signal Analysis.- The Wavelet Transforms and Their Basic Properties.- Multiresolution Analysis and Construction of Wavelets.- Extensions of Multiresolution Analysis.- Newland's Harmonic Wavelets.- Wavelet Transform Analysis of Turbulence.

Rezensionen

"It can be seen as a reference text or as a study book, complete with definitions, theorems, proofs and exercises. ... The book is an up to date reference work on univariate Fourier and wavelet analysis including recent developments in multiresolution, wavelet analysis, and applications in turbulence. The systematic construction of the chapters with extensive lists of exercises make it also very suitable for teaching." (Adhemar Bultheel, euro-math-soc.eu, February, 2015)

"The book is primarily aimed at advanced undergraduates and graduate students across all of applied mathematics. It is a good source of information for all professionals interested in wavelet transforms and their applications." (Yuri A. Farkov, zbMATH 1308.42030, 2015)