Foundations of Signal Processing

Foundations of Signal Processing

Covers state-of-the-art signal processing methods and techniques, and provides a solid foundation for those hoping to advance the theory and practice of signal processing.

Publication date: 31 May 2014

ISBN-10: 110703860X

ISBN-13: 9781107038608

Paperback: 677 pages

Views: 3,079

Type: N/A

Publisher: Cambridge University Press

License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported

Post time: 13 Jul 2016 10:00:00

Foundations of Signal Processing

Foundations of Signal Processing Covers state-of-the-art signal processing methods and techniques, and provides a solid foundation for those hoping to advance the theory and practice of signal processing.
Tag(s): Signal Processing
Publication date: 31 May 2014
ISBN-10: 110703860X
ISBN-13: 9781107038608
Paperback: 677 pages
Views: 3,079
Document Type: N/A
Publisher: Cambridge University Press
License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported
Post time: 13 Jul 2016 10:00:00
Summary/Excerpts of (and not a substitute for) the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported:
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From the Preface:
Goyal, Kovacevic, and Vetterli wrote:Our main goals in this book and its companion volume, Fourier and Wavelet Signal Processing (FWSP) [57], are to enable an understanding of state-of-the-art signal processing methods and techniques, as well as to provide a solid foundation for those hoping to advance the theory and practice of signal processing. We believe that the best way to grasp and internalize the fundamental concepts in signal processing is through the geometry of Hilbert spaces, as this leverages the great innate human capacity for spatial reasoning. While using geometry should ultimately simplify the subject, the connection between signals and geometry is not innate. The reader will have to invest effort to see signals as vectors in Hilbert spaces before reaping the benefits of this view; we believe that effort to be well placed. 


More information is available at the book website.




About The Author(s)


Dr. Goyal  joined the Department of Electrical Engineering and Computer Science of the Massachusetts Institute of Technology in 2004 and currently holds an Esther and Harold E. Edgerton chair.  His research interests include source coding theory, quantization, sampling, and computational imaging.

Vivek K Goyal

Dr. Goyal  joined the Department of Electrical Engineering and Computer Science of the Massachusetts Institute of Technology in 2004 and currently holds an Esther and Harold E. Edgerton chair.  His research interests include source coding theory, quantization, sampling, and computational imaging.


Jelena Kovačević is the David Edward Schramm University Professor and Head of Electrical and Computer Engineering and Professor of Biomedical Engineering at Carnegie Mellon University. Her research interests include biomedical imaging as well as multiresolution techniques such as wavelets and frames.

Jelena Kovačević

Jelena Kovačević is the David Edward Schramm University Professor and Head of Electrical and Computer Engineering and Professor of Biomedical Engineering at Carnegie Mellon University. Her research interests include biomedical imaging as well as multiresolution techniques such as wavelets and frames.


Martin Vetterli is a professor in the Audiovisual Communications Laboratory at École Polytechnique Fédérale De Lausanne (EPFL). His fields of expertise include theory of wavelets and their applications, inverse problems and sparsity, signal processing for communications, and sensor networks.

Martin Vetterli

Martin Vetterli is a professor in the Audiovisual Communications Laboratory at École Polytechnique Fédérale De Lausanne (EPFL). His fields of expertise include theory of wavelets and their applications, inverse problems and sparsity, signal processing for communications, and sensor networks.


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