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Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Functional analysis
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Computational Signal Processing with Wavelets (Paperback, 1st ed. 2017)
Loot Price: R2,291
Discovery Miles 22 910
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Computational Signal Processing with Wavelets (Paperback, 1st ed. 2017)
Series: Modern Birkhauser Classics
Expected to ship within 18 - 22 working days
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This unique resource examines the conceptual, computational, and
practical aspects of applied signal processing using wavelets. With
this book, readers will understand and be able to use the power and
utility of new wavelet methods in science and engineering problems
and analysis. The text is written in a clear, accessible style
avoiding unnecessary abstractions and details. From a computational
perspective, wavelet signal processing algorithms are presented and
applied to signal compression, noise suppression, and signal
identification. Numerical illustrations of these computational
techniques are further provided with interactive software (MATLAB
code) that is available on the World Wide Web. Topics and Features
Continuous wavelet and Gabor transforms Frame-based theory of
discretization and reconstruction of analog signals is developed
New and efficient "overcomplete" wavelet transform is introduced
and applied Numerical illustrations with an object-oriented
computational perspective using the Wavelet Signal Processing
Workstation (MATLAB code) available This book is an excellent
resource for information and computational tools needed to use
wavelets in many types of signal processing problems. Graduates,
professionals, and practitioners in engineering, computer science,
geophysics, and applied mathematics will benefit from using the
book and software tools. The present, softcover reprint is designed
to make this classic textbook available to a wider audience. A
self-contained text that is theoretically rigorous while
maintaining contact with interesting applications. A particularly
noteworthy topic...is a class of 'overcomplete wavelets'. These
functions are not orthonormal and they lead to many useful results.
-Journal of Mathematical Psychology
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