Computational Signal Processing with Wavelets (Modern Birkh�user Classics)
Anthony Teolis
Sold by Chiron Media, Wallingford, United Kingdom
AbeBooks Seller since August 2, 2010
New - Soft cover
Condition: New
Quantity: 10 available
Add to basketSold by Chiron Media, Wallingford, United Kingdom
AbeBooks Seller since August 2, 2010
Condition: New
Quantity: 10 available
Add to basketThe 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
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
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
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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