Concise Signal Models
by Michael Wakin
Publisher: Connexions 2009
Number of pages: 55
This book reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
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This book uses an index map, a polynomial decomposition, an operator factorization, and a conversion to a filter to develop a very general description of fast algorithms to calculate the discrete Fourier transform. Computer programs are provided.
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