Approximate Message Passing Algorithms For Compressed Sensing
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Approximate Message Passing Algorithms For Compressed Sensing
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Author : Mohammad Ali Maleki
language : en
Publisher: Stanford University
Release Date : 2010
Approximate Message Passing Algorithms For Compressed Sensing written by Mohammad Ali Maleki and has been published by Stanford University this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Compressed sensing refers to a growing body of techniques that `undersample' high-dimensional signals and yet recover them accurately. Such techniques make fewer measurements than traditional sampling theory demands: rather than sampling proportional to frequency bandwidth, they make only as many measurements as the underlying `information content' of those signals. However, as compared with traditional sampling theory, which can recover signals by applying simple linear reconstruction formulas, the task of signal recovery from reduced measurements requires nonlinear, and so far, relatively expensive reconstruction schemes. One popular class of reconstruction schemes uses linear programming (LP) methods; there is an elegant theory for such schemes promising large improvements over ordinary sampling rules in recovering sparse signals. However, solving the required LPs is substantially more expensive in applications than the linear reconstruction schemes that are now standard. In certain imaging problems, the signal to be acquired may be an image with $10^6$ pixels and the required LP would involve tens of thousands of constraints and millions of variables. Despite advances in the speed of LP, such methods are still dramatically more expensive to solve than we would like. In this thesis we focus on a class of low computational complexity algorithms known as iterative thresholding. We study them both theoretically and empirically. We will also introduce a new class of algorithms called approximate message passing or AMP. These schemes have several advantages over the classical thresholding approaches. First, they take advantage of the statistical properties of the problem to improve the convergence rate and predictability of the algorithm. Second, the nice properties of these algorithms enable us to make very accurate theoretical predictions on the asymptotic performance of LPs as well. It will be shown that more traditional techniques such as coherence and restricted isometry property are not able to make such precise predictions.
Turbo Message Passing Algorithms For Structured Signal Recovery
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Author : Xiaojun Yuan
language : en
Publisher: Springer Nature
Release Date : 2020-10-13
Turbo Message Passing Algorithms For Structured Signal Recovery written by Xiaojun Yuan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-13 with Technology & Engineering categories.
This book takes a comprehensive study on turbo message passing algorithms for structured signal recovery, where the considered structured signals include 1) a sparse vector/matrix (which corresponds to the compressed sensing (CS) problem), 2) a low-rank matrix (which corresponds to the affine rank minimization (ARM) problem), 3) a mixture of a sparse matrix and a low-rank matrix (which corresponds to the robust principal component analysis (RPCA) problem). The book is divided into three parts. First, the authors introduce a turbo message passing algorithm termed denoising-based Turbo-CS (D-Turbo-CS). Second, the authors introduce a turbo message passing (TMP) algorithm for solving the ARM problem. Third, the authors introduce a TMP algorithm for solving the RPCA problem which aims to recover a low-rank matrix and a sparse matrix from their compressed mixture. With this book, we wish to spur new researches on applying message passing to various inference problems. Provides an in depth look into turbo message passing algorithms for structured signal recovery Includes efficient iterative algorithmic solutions for inference, optimization, and satisfaction problems through message passing Shows applications in areas such as wireless communications and computer vision
Compressed Sensing In Radar Signal Processing
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Author : Antonio De Maio
language : en
Publisher: Cambridge University Press
Release Date : 2019-10-17
Compressed Sensing In Radar Signal Processing written by Antonio De Maio and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-17 with Technology & Engineering categories.
Learn about the most recent theoretical and practical advances in radar signal processing using tools and techniques from compressive sensing. Providing a broad perspective that fully demonstrates the impact of these tools, the accessible and tutorial-like chapters cover topics such as clutter rejection, CFAR detection, adaptive beamforming, random arrays for radar, space-time adaptive processing, and MIMO radar. Each chapter includes coverage of theoretical principles, a detailed review of current knowledge, and discussion of key applications, and also highlights the potential benefits of using compressed sensing algorithms. A unified notation and numerous cross-references between chapters make it easy to explore different topics side by side. Written by leading experts from both academia and industry, this is the ideal text for researchers, graduate students and industry professionals working in signal processing and radar.
Statistical Physics Optimization Inference And Message Passing Algorithms
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Author : Florent Krzakala
language : en
Publisher: Oxford University Press
Release Date : 2016
Statistical Physics Optimization Inference And Message Passing Algorithms written by Florent Krzakala and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Computers categories.
In the last decade, there have been an increasing convergence of interest and methods between theoretical physics and fields as diverse as probability, machine learning, optimization and compressed sensing. In particular, many theoretical and applied works in statistical physics and computer science have relied on the use of message passing algorithms and their connection to statistical physics of spin glasses. The aim of this book, especially adapted to PhD students, post-docs, and young researchers, is to present the background necessary for entering this fast developing field.
Compressed Sensing In Information Processing
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Author : Gitta Kutyniok
language : en
Publisher: Springer Nature
Release Date : 2022-10-20
Compressed Sensing In Information Processing written by Gitta Kutyniok and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-20 with Mathematics categories.
This contributed volume showcases the most significant results obtained from the DFG Priority Program on Compressed Sensing in Information Processing. Topics considered revolve around timely aspects of compressed sensing with a special focus on applications, including compressed sensing-like approaches to deep learning; bilinear compressed sensing - efficiency, structure, and robustness; structured compressive sensing via neural network learning; compressed sensing for massive MIMO; and security of future communication and compressive sensing.
Artificial Intelligence And Evolutionary Computations In Engineering Systems
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Author : Subhransu Sekhar Dash
language : en
Publisher: Springer
Release Date : 2016-02-05
Artificial Intelligence And Evolutionary Computations In Engineering Systems written by Subhransu Sekhar Dash and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-05 with Technology & Engineering categories.
The book is a collection of high-quality peer-reviewed research papers presented in the first International Conference on International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES -2015) held at Velammal Engineering College (VEC), Chennai, India during 22 – 23 April 2015. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of Communication, Computing and Power Technologies.
Excursions In Harmonic Analysis Volume 4
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Author : Radu Balan
language : en
Publisher: Birkhäuser
Release Date : 2015-10-20
Excursions In Harmonic Analysis Volume 4 written by Radu Balan and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-20 with Mathematics categories.
This volume consists of contributions spanning a wide spectrum of harmonic analysis and its applications written by speakers at the February Fourier Talks from 2002 – 2013. Containing cutting-edge results by an impressive array of mathematicians, engineers and scientists in academia, industry and government, it will be an excellent reference for graduate students, researchers and professionals in pure and applied mathematics, physics and engineering. Topics covered include: Special Topics in Harmonic Analysis Applications and Algorithms in the Physical Sciences Gabor Theory RADAR and Communications: Design, Theory, and Applications The February Fourier Talks are held annually at the Norbert Wiener Center for Harmonic Analysis and Applications. Located at the University of Maryland, College Park, the Norbert Wiener Center provides a state-of- the-art research venue for the broad emerging area of mathematical engineering.
Compressed Sensing And Its Applications
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Author : Holger Boche
language : en
Publisher: Birkhäuser
Release Date : 2015-07-04
Compressed Sensing And Its Applications written by Holger Boche and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-04 with Mathematics categories.
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.
An Introduction To Compressed Sensing
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Author : M. Vidyasagar
language : en
Publisher: SIAM
Release Date : 2019-12-03
An Introduction To Compressed Sensing written by M. Vidyasagar and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-03 with Technology & Engineering categories.
Compressed sensing is a relatively recent area of research that refers to the recovery of high-dimensional but low-complexity objects from a limited number of measurements. The topic has applications to signal/image processing and computer algorithms, and it draws from a variety of mathematical techniques such as graph theory, probability theory, linear algebra, and optimization. The author presents significant concepts never before discussed as well as new advances in the theory, providing an in-depth initiation to the field of compressed sensing. An Introduction to Compressed Sensing contains substantial material on graph theory and the design of binary measurement matrices, which is missing in recent texts despite being poised to play a key role in the future of compressed sensing theory. It also covers several new developments in the field and is the only book to thoroughly study the problem of matrix recovery. The book supplies relevant results alongside their proofs in a compact and streamlined presentation that is easy to navigate. The core audience for this book is engineers, computer scientists, and statisticians who are interested in compressed sensing. Professionals working in image processing, speech processing, or seismic signal processing will also find the book of interest.
Compressed Sensing
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Author : Yonina C. Eldar
language : en
Publisher: Cambridge University Press
Release Date : 2012-05-17
Compressed Sensing written by Yonina C. Eldar and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-17 with Mathematics categories.
A detailed presentation of compressed sensing by leading researchers, covering the most significant theoretical and application-oriented advances.