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Wavelets: Theory, Algorithms, and Applications
 
 
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Wavelets: Theory, Algorithms, and Applications [Hardcover]

Laura Montefusco (Editor), Luigia Puccio (Editor), Charles K. Chui (Editor)
3.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

December 2, 1994 0121745759 978-0121745752
Wavelets: Theory, Algorithms, and Applications is the fifth volume in the highly respected series, WAVELET ANALYSIS AND ITS APPLICATIONS. This volume shows why wavelet analysis has become a tool of choice infields ranging from image compression, to signal detection and analysis in electrical engineering and geophysics, to analysis of turbulent or intermittent processes. The 28 papers comprising this volume are organized into seven subject areas: multiresolution analysis, wavelet transforms, tools for time-frequency analysis, wavelets and fractals, numerical methods and algorithms, and applications. More than 135 figures supplement the text.

Features theory, techniques, and applications
Presents alternative theoretical approaches including multiresolution analysis, splines, minimum entropy, and fractal aspects
Contributors cover a broad range of approaches and applications

Editorial Reviews

Review

"...this book goes far deeper into this topic than you normally need it for the use in astronomy, but is a very good written textbook that allows you to look ahead on the general topic of wavelet analysis."
--REVIEWS OF ASTRONOMICAL TOOLS
This volume provides an excellent snapshot of the broad activity in wavelet theory.
--MATHEMATICS OF COMPUTATION

From the Back Cover

Wavelets: Theory, Algorithms, and Applications is the fifth volume in the highly respected series, WAVELET ANALYSIS AND ITS APPLICATIONS. This volume shows why wavelet analysis has become a tool of choice infields ranging from image compression, to signal detection and analysis in electrical engineering and geophysics, to analysis of turbulent or intermittent processes.

The twenty-eight contributors convey their enthusiam for wavelets and their potential applications in increasingly diverse fields. The book is organized into seven sharply focused sections, beginning with multiresolution analysis, the most powerful tool for constructing wavelets. Other topics include wavelet transoforms, tools for time-frequenct analysis, wavelets and fractals, numerical methods and algorithms, and applications. Nore than 135 informative figures and a full-color insert to supplement the text.

Product Details

  • Hardcover: 627 pages
  • Publisher: Academic Press (December 2, 1994)
  • Language: English
  • ISBN-10: 0121745759
  • ISBN-13: 978-0121745752
  • Product Dimensions: 9.3 x 6.2 x 1.3 inches
  • Shipping Weight: 2.4 pounds (View shipping rates and policies)
  • Average Customer Review: 3.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #7,428,035 in Books (See Top 100 in Books)

 

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5 of 5 people found the following review helpful:
3.0 out of 5 stars High quality math papers from a conference, a bit outdated, May 15, 2000
By A Customer
This review is from: Wavelets: Theory, Algorithms, and Applications (Hardcover)
This book consists of some well-written papers by some leading research scientists in the field of wavelets. It can be thought of as a very high quality proceedings book. The title is a bit misleading. The book is mostly about theory and algorithms. A high level of mathematical background is required to read the book. Some books which can be considered competitors to this one are the 2 older and even more outdated books edited by: (1) Combes et al. and (2) Ruskai et al. AND a book by Benedetto and Frazier, which was so successful that it was translated into Japanese (alhtough some of the weaker papers were omitted in the Japanese version). This Chui book and the Benedetto-Frazier book contain extensive references, though many are now out-of-date. The applications section is also bit out-of-date. Mathematics can live on as is, though tastes and fashions vary over time.

Chui is a very successful organizer of conferences and has written and edited many books, either alone or with others. This book is well put together and suffers from fewer faults as Chui's earlier book (Vol 2. of this series).

The theoretical papers are more interesting and cover topics not found in Daubechies' famous book: Ten Lectures on Wavelets. Some of the applications address genuine laboratory problems. Image and acoustical digital signal processing are barely touched upon, but it doesn't matter since the publication of Mallat's A Wavelet Tour of Signal Processing obviates the need. This book does not contain problems to be assigned for homework, but it can still be used in a course -- perhaps a graduate seminar or a special topics course. Be warned that the book is a bit pricey to use as a supplementary text in a course.

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Inside This Book (learn more)
First Sentence:
Orthonormal bases of wavelets and wavelet packets yield linear, non-redundant time-scale and time-frequency decompositions for arbitrary functions and signals. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
local cosine coefficients, shifted orthogonality conditions, vorticity field reconstructed, selfsimilar functions, orthogonal pursuit, segmentation pursuit, multiresolution operator, multiplicity wavelets, periodic spline wavelets, vorticity field corresponding, mean value jump, local cosine transform, segmented transforms, wavelet packet coefficients, phase space atoms, wavelet matrices, dictionary noise, radial power spectrum, wavelet matrix, bidimensional wavelet bases, biorthogonal pair, local cosines, pursuit map, wavelet packet basis, dictionary vectors
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Academic Press, Laura Montefusco, Luigia Puccio, New York, Harmonic Anal, Pure Appl, Flinders University, Université Paris, Editions Frontières, Englewood Cliffs, Laplacian of Gaussian, Paris Cedex, Pattern Anal, Recent Advances, Springer Verlag, Transform Segmented, Different Perspectives, Editions Frontieres, Enstrophy Wavelet, Exact Cover, Introduction Wavelet, Machine Intel, New Jersey, Prentice Hall, Sakakibara Figure
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