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Compressed Sensing and its Applications

Second International MATHEON Conference 2015

  • Book
  • © 2017

Overview

Editors:
  1. Holger Boche

    1. Fakultät für Elektrotechnik und Informationstechnik, Technische Universität München, Munich, Bavaria, Germany

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  2. Giuseppe Caire

    1. Institut für Telekommunikationssysteme, Technische Universität Berlin, Berlin, Germany

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  3. Robert Calderbank

    1. Department of Electrical & Computer Engineering, Duke University, Durham, USA

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  4. Maximilian März

    1. Institut für Mathematik, Technische Universität Berlin, Berlin, Germany

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  5. Gitta Kutyniok

    1. Institut für Mathematik, Technische Universität Berlin, Berlin, Germany

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  6. Rudolf Mathar

    1. Lehrstuhl und Institute für Statistik, RWTH Aachen, Aachen, Germany

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  • Explores many of the novel applications of compressed sensing developed since the previous MATHEON Workshop in 2013
  • Chapters written by leading researchers in compressed sensing with backgrounds in mathematics, computer science, and engineering
  • A thorough introduction to compressed sensing provided for readers who may not be familiar with it
  • Will appeal to a broad audience with research in areas ranging from applied mathematics, signal processing, and electrical engineering to computer science, image sciences, and sparse approximation

Part of the book series: Applied and Numerical Harmonic Analysis (ANHA)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xix
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  2. On the Global-Local Dichotomy in Sparsity Modeling

    • Dmitry Batenkov, Yaniv Romano, Michael Elad
    Pages 1-53

  3. Fourier Phase Retrieval: Uniqueness and Algorithms

    • Tamir Bendory, Robert Beinert, Yonina C. Eldar
    Pages 55-91

  4. Compressed Sensing Approaches for Polynomial Approximation of High-Dimensional Functions

    • Ben Adcock, Simone Brugiapaglia, Clayton G. Webster
    Pages 93-124

  5. Multisection in the Stochastic Block Model Using Semidefinite Programming

    • Naman Agarwal, Afonso S. Bandeira, Konstantinos Koiliaris, Alexandra Kolla
    Pages 125-162

  6. Recovering Signals with Unknown Sparsity in Multiple Dictionaries

    • Rizwan Ahmad, Philip Schniter
    Pages 163-195

  7. Compressive Classification and the Rare Eclipse Problem

    • Afonso S. Bandeira, Dustin G. Mixon, Benjamin Recht
    Pages 197-220

  8. Weak Phase Retrieval

    • Sara Botelho-Andrade, Peter G. Casazza, Dorsa Ghoreishi, Shani Jose, Janet C. Tremain
    Pages 221-234

  9. Cubatures on Grassmannians: Moments, Dimension Reduction, and Related Topics

    • Anna Breger, Martin Ehler, Manuel Gräf, Thomas Peter
    Pages 235-259

  10. A Randomized Tensor Train Singular Value Decomposition

    • Benjamin Huber, Reinhold Schneider, Sebastian Wolf
    Pages 261-290

  11. Versatile and Scalable Cosparse Methods for Physics-Driven Inverse Problems

    • Srđan Kitić, Siouar Bensaid, Laurent Albera, Nancy Bertin, Rémi Gribonval
    Pages 291-332

  12. Total Variation Minimization in Compressed Sensing

    • Felix Krahmer, Christian Kruschel, Michael Sandbichler
    Pages 333-358

  13. Compressed Sensing in Hilbert Spaces

    • Yann Traonmilin, Gilles Puy, Rémi Gribonval, Mike E. Davies
    Pages 359-384

  14. Back Matter

    Pages 385-388
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Keywords

About this book

This contributed volume contains articles written by the plenary and invited speakers from the second international MATHEON Workshop 2015 that focus on applications of compressed sensing. Article authors address their techniques for solving the problems of compressed sensing, as well as connections to related areas like detecting community-like structures in graphs, curbatures on Grassmanians, and randomized tensor train singular value decompositions. Some of the novel applications covered include dimensionality reduction, information theory, random matrices, sparse approximation, and sparse recovery. 

This 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 exploring the potential applications for the novel methodology of compressed sensing. An introduction to the subject of compressed sensing is also provided for researchers interested in the field who are not as familiar with it. 

Editors and Affiliations

  • Fakultät für Elektrotechnik und Informationstechnik, Technische Universität München, Munich, Bavaria, Germany

    Holger Boche

  • Institut für Telekommunikationssysteme, Technische Universität Berlin, Berlin, Germany

    Giuseppe Caire

  • Department of Electrical & Computer Engineering, Duke University, Durham, USA

    Robert Calderbank

  • Institut für Mathematik, Technische Universität Berlin, Berlin, Germany

    Maximilian März, Gitta Kutyniok

  • Lehrstuhl und Institute für Statistik, RWTH Aachen, Aachen, Germany

    Rudolf Mathar

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