Compressed Sensing and its Applications: MATHEON Workshop 2013

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Since publication of the initial papers in 2006, compressed sensing has captured the imagination of the international signal processing community, and the mathematical foundations are nowadays quite well understood.

Parallel to the progress in mathematics, the potential applications of compressed sensing have been explored by many international groups of, in particular, engineers and applied mathematicians, achieving very promising advances in various areas such as communication theory, imaging sciences, optics, radar technology, sensor networks, or tomography.

Since many applications have reached a mature state, the research center MATHEON in Berlin focusing on "Mathematics for Key Technologies", invited leading researchers on applications of compressed sensing from mathematics, computer science, and engineering to the "MATHEON Workshop 2013: Compressed Sensing and its Applications” in December 2013. It was the first workshop specifically focusing on the applications of compressed sensing. This book features contributions by the plenary and invited speakers of this workshop.

To make this book accessible for those unfamiliar with compressed sensing, the book will not only contain chapters on various applications of compressed sensing written by plenary and invited speakers, but will also provide a general introduction into compressed sensing.

The book is aimed at both graduate students and researchers in the areas of applied mathematics, computer science, and engineering as well as other applied scientists interested in the potential and applications of the novel methodology of compressed sensing. For those readers who are not already familiar with compressed sensing, an introduction to the basics of this theory will be included.

Author(s): Holger Boche, Robert Calderbank, Gitta Kutyniok, Jan Vybíral (eds.)
Series: Applied and Numerical Harmonic Analysis
Edition: 1
Publisher: Birkhäuser Basel
Year: 2015

Language: English
Pages: 472
Tags: Information and Communication, Circuits; Signal, Image and Speech Processing; Coding and Information Theory; Numerical Analysis; Linear and Multilinear Algebras, Matrix Theory; Computational Science and Engineering

Front Matter....Pages i-xii
A Survey of Compressed Sensing....Pages 1-39
Temporal Compressive Sensing for Video....Pages 41-74
Compressed Sensing, Sparse Inversion, and Model Mismatch....Pages 75-95
Recovering Structured Signals in Noise: Least-Squares Meets Compressed Sensing....Pages 97-141
The Quest for Optimal Sampling: Computationally Efficient, Structure-Exploiting Measurements for Compressed Sensing....Pages 143-167
Compressive Sensing in Acoustic Imaging....Pages 169-192
Quantization and Compressive Sensing....Pages 193-237
Compressive Gaussian Mixture Estimation....Pages 239-258
Two Algorithms for Compressed Sensing of Sparse Tensors....Pages 259-281
Sparse Model Uncertainties in Compressed Sensing with Application to Convolutions and Sporadic Communication....Pages 283-313
Cosparsity in Compressed Sensing....Pages 315-339
Structured Sparsity: Discrete and Convex Approaches....Pages 341-387
Explicit Matrices with the Restricted Isometry Property: Breaking the Square-Root Bottleneck....Pages 389-417
Tensor Completion in Hierarchical Tensor Representations....Pages 419-450
Compressive Classification: Where Wireless Communications Meets Machine Learning....Pages 451-468
Back Matter....Pages 469-472