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Compressed Sensing and its Applications : Second International MATHEON Conference 2015 / edited by Holger Boche, Giuseppe Caire, Robert Calderbank, Maximilian März, Gitta Kutyniok, Rudolf Mathar.

Springer Nature - Springer Mathematics and Statistics eBooks 2017 English International Available online

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Format:
Book
Contributor:
Boche, Holger.., Editor.
Caire, Giuseppe.., Editor.
Calderbank, Robert.., Editor.
März, Maximilian.., Editor.
Kutyniok, Gitta.., Editor.
Mathar, Rudolf.., Editor.
Series:
Applied and Numerical Harmonic Analysis, 2296-5009
Language:
English
Subjects (All):
Information theory.
Numerical analysis.
Signal processing.
Image processing.
Speech processing systems.
Coding theory.
Matrix theory.
Algebra.
Computer science--Mathematics.
Computer science.
Information and Communication, Circuits.
Numerical Analysis.
Signal, Image and Speech Processing.
Coding and Information Theory.
Linear and Multilinear Algebras, Matrix Theory.
Computational Science and Engineering.
Local Subjects:
Information and Communication, Circuits.
Numerical Analysis.
Signal, Image and Speech Processing.
Coding and Information Theory.
Linear and Multilinear Algebras, Matrix Theory.
Computational Science and Engineering.
Physical Description:
1 online resource (XIX, 388 p. 77 illus., 57 illus. in color.)
Edition:
1版. 2017.
Place of Publication:
Cham : Springer International Publishing : Imprint: Birkhäuser, 2017.
Summary:
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. .
Contents:
Preface
On the Global-Local Dichotomy in Sparsity Modeling, Batenkov, Romano, Elad
Fourier Phase Retrieval: Uniqueness and Algorithms, Bendory, Beinert, Eldar
Compressed Sensing Approaches for Polynomial Approximation of High-Dimensional Functions, Adcock, Brugiapaglia, Webster
Multisection in the Stochastic Block Model using Semidefinite Programming, Agarwal, Bandeira, Koiliaris, Kolla
Recovering Signals with Unknown Sparsity in Multiple Dictionaries, Ahmad, Schniter
Compressive Classification and the Rare Eclipse Problem, Bandeira, Mixon, Recht
Weak Phase Retrieval, Bothelo-Andrade, Casazza, Ghoreishi, Jose, Tremain
Cubatures on Grassmannians: Moments, Dimension Reduction, and Related Topics, Breger, Ehler, Gräf, Peter
A Randomized Tensor Train Singular Value Decomposition, Huber, Schneider, Wolf
Versatile and Scalable Cosparse Methods for Phsyics-driven Inverse Problems, Kitić, Bensiad, Albera, Bertin, Gribonval
Total Variation Minimization in Compressed Sensing, Felix Krahmer, Kruschel, Sandbichler
Compressed Sensing in Hilbert Spaces, Traonmilin, Puy, Gribonval, Davies.
Notes:
Includes bibliographical references at the end of each chapters.
ISBN:
3-319-69802-8

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