Compressed Sensing With Side Information On The Feasible Region

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Compressed Sensing with Side Information on the Feasible Region

Author : Mohammad Rostami
Publisher : Springer
ISBN 13 : 3319003666
Total Pages : 77 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Compressed Sensing with Side Information on the Feasible Region by : Mohammad Rostami

Download or read book Compressed Sensing with Side Information on the Feasible Region written by Mohammad Rostami and published by Springer. This book was released on 2013-05-15 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses compressive sensing in the presence of side information. Compressive sensing is an emerging technique for efficiently acquiring and reconstructing a signal. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. The side information can be about the source structure, distribution, etc. Such cases can be viewed as extensions of the classical CS. In these cases we are interested in incorporating the side information to either improve the quality of the source reconstruction or decrease the number of samples required for accurate reconstruction. In this book we assume availability of side information about the feasible region. The main applications investigated are image deblurring for optical imaging, 3D surface reconstruction, and reconstructing spatiotemporally correlated sources. The author shows that the side information can be used to improve the quality of the reconstruction compared to the classic compressive sensing. The book will be of interest to all researchers working on compressive sensing, inverse problems, and image processing.

Compressive Sensing of Earth Observations

Author : C.H. Chen
Publisher : CRC Press
ISBN 13 : 1351650653
Total Pages : 727 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Compressive Sensing of Earth Observations by : C.H. Chen

Download or read book Compressive Sensing of Earth Observations written by C.H. Chen and published by CRC Press. This book was released on 2017-05-25 with total page 727 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future remote sensing systems will make extensive use of Compressive Sensing (CS) as it becomes more integrated into the system design with increased high resolution sensor developments and the rising earth observation data generated each year. Written by leading experts in the field Compressive Sensing of Earth Observations provides a comprehensive and balanced coverage of the theory and applications of CS in all aspects of earth observations. This work covers a myriad of practical aspects such as the use of CS in detection of human vital signs in a cluttered environment and the corresponding modeling of rib-cage breathing. Readers are also presented with three different applications of CS to the ISAR imaging problem, which includes image reconstruction from compressed data, resolution enhancement, and image reconstruction from incomplete data.

Handbook of Mathematical Methods in Imaging

Author : Otmar Scherzer
Publisher : Springer Science & Business Media
ISBN 13 : 0387929193
Total Pages : 1626 pages
Book Rating : 4.3/5 (879 download)

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Book Synopsis Handbook of Mathematical Methods in Imaging by : Otmar Scherzer

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.

A Mathematical Introduction to Compressive Sensing

Author : Simon Foucart
Publisher : Springer Science & Business Media
ISBN 13 : 0817649484
Total Pages : 634 pages
Book Rating : 4.8/5 (176 download)

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Book Synopsis A Mathematical Introduction to Compressive Sensing by : Simon Foucart

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.

An Introduction to Compressed Sensing

Author : M. Vidyasagar
Publisher : SIAM
ISBN 13 : 161197612X
Total Pages : 354 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis An Introduction to Compressed Sensing by : M. Vidyasagar

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 354 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.

Transfer Learning through Embedding Spaces

Author : Mohammad Rostami
Publisher : CRC Press
ISBN 13 : 1000400573
Total Pages : 221 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Transfer Learning through Embedding Spaces by : Mohammad Rostami

Download or read book Transfer Learning through Embedding Spaces written by Mohammad Rostami and published by CRC Press. This book was released on 2021-06-28 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent progress in artificial intelligence (AI) has revolutionized our everyday life. Many AI algorithms have reached human-level performance and AI agents are replacing humans in most professions. It is predicted that this trend will continue and 30% of work activities in 60% of current occupations will be automated. This success, however, is conditioned on availability of huge annotated datasets to training AI models. Data annotation is a time-consuming and expensive task which still is being performed by human workers. Learning efficiently from less data is a next step for making AI more similar to natural intelligence. Transfer learning has been suggested a remedy to relax the need for data annotation. The core idea in transfer learning is to transfer knowledge across similar tasks and use similarities and previously learned knowledge to learn more efficiently. In this book, we provide a brief background on transfer learning and then focus on the idea of transferring knowledge through intermediate embedding spaces. The idea is to couple and relate different learning through embedding spaces that encode task-level relations and similarities. We cover various machine learning scenarios and demonstrate that this idea can be used to overcome challenges of zero-shot learning, few-shot learning, domain adaptation, continual learning, lifelong learning, and collaborative learning.

Sparse representation of visual data for compression and compressed sensing

Author : Ehsan Miandji
Publisher : Linköping University Electronic Press
ISBN 13 : 9176851869
Total Pages : 180 pages
Book Rating : 4.1/5 (768 download)

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Book Synopsis Sparse representation of visual data for compression and compressed sensing by : Ehsan Miandji

Download or read book Sparse representation of visual data for compression and compressed sensing written by Ehsan Miandji and published by Linköping University Electronic Press. This book was released on 2018-11-23 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ongoing advances in computational photography have introduced a range of new imaging techniques for capturing multidimensional visual data such as light fields, BRDFs, BTFs, and more. A key challenge inherent to such imaging techniques is the large amount of high dimensional visual data that is produced, often requiring GBs, or even TBs, of storage. Moreover, the utilization of these datasets in real time applications poses many difficulties due to the large memory footprint. Furthermore, the acquisition of large-scale visual data is very challenging and expensive in most cases. This thesis makes several contributions with regards to acquisition, compression, and real time rendering of high dimensional visual data in computer graphics and imaging applications. Contributions of this thesis reside on the strong foundation of sparse representations. Numerous applications are presented that utilize sparse representations for compression and compressed sensing of visual data. Specifically, we present a single sensor light field camera design, a compressive rendering method, a real time precomputed photorealistic rendering technique, light field (video) compression and real time rendering, compressive BRDF capture, and more. Another key contribution of this thesis is a general framework for compression and compressed sensing of visual data, regardless of the dimensionality. As a result, any type of discrete visual data with arbitrary dimensionality can be captured, compressed, and rendered in real time. This thesis makes two theoretical contributions. In particular, uniqueness conditions for recovering a sparse signal under an ensemble of multidimensional dictionaries is presented. The theoretical results discussed here are useful for designing efficient capturing devices for multidimensional visual data. Moreover, we derive the probability of successful recovery of a noisy sparse signal using OMP, one of the most widely used algorithms for solving compressed sensing problems.

Compressed Sensing

Author : Yonina C. Eldar
Publisher : Cambridge University Press
ISBN 13 : 1107394392
Total Pages : 557 pages
Book Rating : 4.1/5 (73 download)

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Book Synopsis Compressed Sensing by : Yonina C. Eldar

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: Compressed sensing is an exciting, rapidly growing field, attracting considerable attention in electrical engineering, applied mathematics, statistics and computer science. This book provides the first detailed introduction to the subject, highlighting theoretical advances and a range of applications, as well as outlining numerous remaining research challenges. After a thorough review of the basic theory, many cutting-edge techniques are presented, including advanced signal modeling, sub-Nyquist sampling of analog signals, non-asymptotic analysis of random matrices, adaptive sensing, greedy algorithms and use of graphical models. All chapters are written by leading researchers in the field, and consistent style and notation are utilized throughout. Key background information and clear definitions make this an ideal resource for researchers, graduate students and practitioners wanting to join this exciting research area. It can also serve as a supplementary textbook for courses on computer vision, coding theory, signal processing, image processing and algorithms for efficient data processing.

Beyond the Worst-Case Analysis of Algorithms

Author : Tim Roughgarden
Publisher : Cambridge University Press
ISBN 13 : 1108494315
Total Pages : 705 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Beyond the Worst-Case Analysis of Algorithms by : Tim Roughgarden

Download or read book Beyond the Worst-Case Analysis of Algorithms written by Tim Roughgarden and published by Cambridge University Press. This book was released on 2021-01-14 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces exciting new methods for assessing algorithms for problems ranging from clustering to linear programming to neural networks.

Algorithmic Aspects of Machine Learning

Author : Ankur Moitra
Publisher : Cambridge University Press
ISBN 13 : 1107184584
Total Pages : 161 pages
Book Rating : 4.1/5 (71 download)

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Book Synopsis Algorithmic Aspects of Machine Learning by : Ankur Moitra

Download or read book Algorithmic Aspects of Machine Learning written by Ankur Moitra and published by Cambridge University Press. This book was released on 2018-09-27 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces cutting-edge research on machine learning theory and practice, providing an accessible, modern algorithmic toolkit.

Foundations of Data Science

Author : Avrim Blum
Publisher : Cambridge University Press
ISBN 13 : 1108617360
Total Pages : 433 pages
Book Rating : 4.1/5 (86 download)

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Book Synopsis Foundations of Data Science by : Avrim Blum

Download or read book Foundations of Data Science written by Avrim Blum and published by Cambridge University Press. This book was released on 2020-01-23 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.

Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms

Author : Bhabesh Deka
Publisher : Springer
ISBN 13 : 9811335974
Total Pages : 133 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms by : Bhabesh Deka

Download or read book Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms written by Bhabesh Deka and published by Springer. This book was released on 2018-12-29 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive review of the recent developments in fast L1-norm regularization-based compressed sensing (CS) magnetic resonance image reconstruction algorithms. Compressed sensing magnetic resonance imaging (CS-MRI) is able to reduce the scan time of MRI considerably as it is possible to reconstruct MR images from only a few measurements in the k-space; far below the requirements of the Nyquist sampling rate. L1-norm-based regularization problems can be solved efficiently using the state-of-the-art convex optimization techniques, which in general outperform the greedy techniques in terms of quality of reconstructions. Recently, fast convex optimization based reconstruction algorithms have been developed which are also able to achieve the benchmarks for the use of CS-MRI in clinical practice. This book enables graduate students, researchers, and medical practitioners working in the field of medical image processing, particularly in MRI to understand the need for the CS in MRI, and thereby how it could revolutionize the soft tissue imaging to benefit healthcare technology without making major changes in the existing scanner hardware. It would be particularly useful for researchers who have just entered into the exciting field of CS-MRI and would like to quickly go through the developments to date without diving into the detailed mathematical analysis. Finally, it also discusses recent trends and future research directions for implementation of CS-MRI in clinical practice, particularly in Bio- and Neuro-informatics applications.

High-Dimensional Probability

Author : Roman Vershynin
Publisher : Cambridge University Press
ISBN 13 : 1108415199
Total Pages : 299 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis High-Dimensional Probability by : Roman Vershynin

Download or read book High-Dimensional Probability written by Roman Vershynin and published by Cambridge University Press. This book was released on 2018-09-27 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

Mixtures

Author : Kerrie L. Mengersen
Publisher : John Wiley & Sons
ISBN 13 : 1119998441
Total Pages : 352 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Mixtures by : Kerrie L. Mengersen

Download or read book Mixtures written by Kerrie L. Mengersen and published by John Wiley & Sons. This book was released on 2011-05-03 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component distributions of the mixture; the distributions may be continuous or discrete. The editors provide a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions along with MCMC computational methods, together with a range of detailed discussions covering the applications of the methods and features chapters from the leading experts on the subject. The applications are drawn from scientific discipline, including biostatistics, computer science, ecology and finance. This area of statistics is important to a range of disciplines, and its methodology attracts interest from researchers in the fields in which it can be applied.

Sparse Representations for Radar with MATLAB® Examples

Author : Peter Knee
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1627050345
Total Pages : 88 pages
Book Rating : 4.6/5 (27 download)

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Book Synopsis Sparse Representations for Radar with MATLAB® Examples by : Peter Knee

Download or read book Sparse Representations for Radar with MATLAB® Examples written by Peter Knee and published by Morgan & Claypool Publishers. This book was released on 2012 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB(R) examples to emphasize the practical implementations both inside and outside the radar field.

Geographic Information Systems, Photogrammetry, and Geological/geophysical Remote Sensing

Author : James J. Pearson
Publisher :
ISBN 13 :
Total Pages : 218 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Geographic Information Systems, Photogrammetry, and Geological/geophysical Remote Sensing by : James J. Pearson

Download or read book Geographic Information Systems, Photogrammetry, and Geological/geophysical Remote Sensing written by James J. Pearson and published by . This book was released on 1995 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Intelligent Systems Design and Applications

Author : Ajith Abraham
Publisher : Springer
ISBN 13 : 3030166600
Total Pages : 1135 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Intelligent Systems Design and Applications by : Ajith Abraham

Download or read book Intelligent Systems Design and Applications written by Ajith Abraham and published by Springer. This book was released on 2019-04-13 with total page 1135 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent research on Intelligent Systems and Nature Inspired Computing. It presents 212 selected papers from the 18th International Conference on Intelligent Systems Design and Applications (ISDA 2018) and the 10th World Congress on Nature and Biologically Inspired Computing (NaBIC), which was held at VIT University, India. ISDA-NaBIC 2018 was a premier conference in the field of Computational Intelligence and brought together researchers, engineers and practitioners whose work involved intelligent systems and their applications in industry and the “real world.” Including contributions by authors from over 40 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.