Download Concise Signal Models by Michael Wakin, Concise Signal Models 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.


Table of Contents

1 Introduction to Concise Signal Models
2 Signal Dictionaries and Representations
3 Manifolds
4 Low-Dimensional Signal Models
5 Approximation
6 Compression
7 Dimensionality Reduction
8 Compressed Sensing