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Compressed Sensing and its Applications: Second International MATHEON Conference 2015 de Holger Boche

Compressed Sensing and its Applications: Second International MATHEON Conference 2015: Applied and Numerical Harmonic Analysis

Editat de Holger Boche, Giuseppe Caire, Robert Calderbank, Maximilian März, Gitta Kutyniok, Rudolf Mathar
en Limba Engleză Hardback – 26 ian 2018
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. 
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Specificații

ISBN-13: 9783319698014
ISBN-10: 331969801X
Pagini: 398
Ilustrații: XIX, 388 p. 77 illus., 57 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.75 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Birkhäuser
Seria Applied and Numerical Harmonic Analysis

Locul publicării:Cham, Switzerland

Cuprins

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.

Textul de pe ultima copertă

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 thefield who are not as familiar with it. 

Caracteristici

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