Compressed Sensing And Its Applications

Author : Yonina C. Eldar
Publisher : Cambridge University Press
ISBN 13 : 1107005582
Total Pages : 557 pages
Book Rating : 4.87/5 ( download)

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Download or read book Compressed Sensing written by Yonina C. Eldar and published by Cambridge University Press. This book was released on 2012-05-17 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed presentation of compressed sensing by leading researchers, covering the most significant theoretical and application-oriented advances.

Author : Holger Boche
Publisher : Birkhäuser
ISBN 13 : 9783319347622
Total Pages : 0 pages
Book Rating : 4.24/5 ( download)

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Download or read book Compressed Sensing and its Applications written by Holger Boche and published by Birkhäuser. This book was released on 2016-10-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : M. Vidyasagar
Publisher : SIAM
ISBN 13 : 161197612X
Total Pages : 341 pages
Book Rating : 4.20/5 ( download)

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Download or read book An Introduction to Compressed Sensing written by M. Vidyasagar and published by SIAM. This book was released on 2019-12-03 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Antonio De Maio
Publisher : Cambridge University Press
ISBN 13 : 110857694X
Total Pages : 381 pages
Book Rating : 4.49/5 ( download)

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Download or read book Compressed Sensing in Radar Signal Processing written by Antonio De Maio and published by Cambridge University Press. This book was released on 2019-10-17 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Holger Boche
Publisher : Birkhäuser
ISBN 13 : 3319160427
Total Pages : 472 pages
Book Rating : 4.29/5 ( download)

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Download or read book Compressed Sensing and its Applications written by Holger Boche and published by Birkhäuser. This book was released on 2015-07-04 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Otmar Scherzer
Publisher : Springer Science & Business Media
ISBN 13 : 0387929193
Total Pages : 1626 pages
Book Rating : 4.94/5 ( download)

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Download or read book Handbook of Mathematical Methods in Imaging written by Otmar Scherzer and published by Springer Science & Business Media. This book was released on 2010-11-23 with total page 1626 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.

Author : Avishy Y. Carmi
Publisher : Springer Science & Business Media
ISBN 13 : 364238398X
Total Pages : 505 pages
Book Rating : 4.84/5 ( download)

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Download or read book Compressed Sensing & Sparse Filtering written by Avishy Y. Carmi and published by Springer Science & Business Media. This book was released on 2013-09-13 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and limited data. One such trend that recently gained popularity and to some extent revolutionised signal processing is compressed sensing. Compressed sensing builds upon the observation that many signals in nature are nearly sparse (or compressible, as they are normally referred to) in some domain, and consequently they can be reconstructed to within high accuracy from far fewer observations than traditionally held to be necessary. Apart from compressed sensing this book contains other related approaches. Each methodology has its own formalities for dealing with such problems. As an example, in the Bayesian approach, sparseness promoting priors such as Laplace and Cauchy are normally used for penalising improbable model variables, thus promoting low complexity solutions. Compressed sensing techniques and homotopy-type solutions, such as the LASSO, utilise l1-norm penalties for obtaining sparse solutions using fewer observations than conventionally needed. The book emphasizes on the role of sparsity as a machinery for promoting low complexity representations and likewise its connections to variable selection and dimensionality reduction in various engineering problems. This book is intended for researchers, academics and practitioners with interest in various aspects and applications of sparse signal processing.

Author : Simon Foucart
Publisher : Springer Science & Business Media
ISBN 13 : 0817649484
Total Pages : 634 pages
Book Rating : 4.87/5 ( download)

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Download or read book A Mathematical Introduction to Compressive Sensing written by Simon Foucart and published by Springer Science & Business Media. This book was released on 2013-08-13 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: At the intersection of mathematics, engineering, and computer science sits the thriving field of compressive sensing. Based on the premise that data acquisition and compression can be performed simultaneously, compressive sensing finds applications in imaging, signal processing, and many other domains. In the areas of applied mathematics, electrical engineering, and theoretical computer science, an explosion of research activity has already followed the theoretical results that highlighted the efficiency of the basic principles. The elegant ideas behind these principles are also of independent interest to pure mathematicians. A Mathematical Introduction to Compressive Sensing gives a detailed account of the core theory upon which the field is build. With only moderate prerequisites, it is an excellent textbook for graduate courses in mathematics, engineering, and computer science. It also serves as a reliable resource for practitioners and researchers in these disciplines who want to acquire a careful understanding of the subject. A Mathematical Introduction to Compressive Sensing uses a mathematical perspective to present the core of the theory underlying compressive sensing.

Author : Mahdi Khosravy
Publisher : Academic Press
ISBN 13 : 0128212489
Total Pages : 308 pages
Book Rating : 4.86/5 ( download)

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Download or read book Compressive Sensing in Healthcare written by Mahdi Khosravy and published by Academic Press. This book was released on 2020-05-18 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Compressive Sensing in Healthcare, part of the Advances in Ubiquitous Sensing Applications for Healthcare series gives a review on compressive sensing techniques in a practical way, also presenting deterministic compressive sensing techniques that can be used in the field. The focus of the book is on healthcare applications for this technology. It is intended for both the creators of this technology and the end users of these products. The content includes the use of EEG and ECG, plus hardware and software requirements for building projects. Body area networks and body sensor networks are explored. Provides a toolbox for compressive sensing in health, presenting both mathematical and coding information Presents an intuitive introduction to compressive sensing, including MATLAB tutorials Covers applications of compressive sensing in health care

Author : Holger Boche
Publisher : Birkhäuser
ISBN 13 : 3319730746
Total Pages : 305 pages
Book Rating : 4.45/5 ( download)

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Download or read book Compressed Sensing and Its Applications written by Holger Boche and published by Birkhäuser. This book was released on 2019-08-13 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin. In addition to methods in compressed sensing, chapters provide insights into cutting edge applications of deep learning in data science, highlighting the overlapping ideas and methods that connect the fields of compressed sensing and deep learning. Specific topics covered include: Quantized compressed sensing Classification Machine learning Oracle inequalities Non-convex optimization Image reconstruction Statistical learning theory This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing.