An Introduction to Compressed Sensing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook An Introduction to Compressed Sensing write by M. Vidyasagar. This book was released on 2019-12-03. An Introduction to Compressed Sensing available in PDF, EPUB and Kindle. 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.
A Mathematical Introduction to Compressive Sensing
A Mathematical Introduction to Compressive Sensing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook A Mathematical Introduction to Compressive Sensing write by Simon Foucart. This book was released on 2013-08-13. A Mathematical Introduction to Compressive Sensing available in PDF, EPUB and Kindle. 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.
Compressed Sensing & Sparse Filtering
Compressed Sensing & Sparse Filtering - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Compressed Sensing & Sparse Filtering write by Avishy Y. Carmi. This book was released on 2013-09-13. Compressed Sensing & Sparse Filtering available in PDF, EPUB and Kindle. 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.
Handbook of Mathematical Methods in Imaging
Handbook of Mathematical Methods in Imaging - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of Mathematical Methods in Imaging write by Otmar Scherzer. This book was released on 2010-11-23. Handbook of Mathematical Methods in Imaging available in PDF, EPUB and Kindle. 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.
An Introduction to Compressed Sensing
An Introduction to Compressed Sensing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook An Introduction to Compressed Sensing write by Mathukumalli Vidyasagar. This book was released on 2020. An Introduction to Compressed Sensing available in PDF, EPUB and Kindle. "The intended audience for the book consists of those who are interested in applying the theory of compressed sensing to practical problems, as well as those whose aim is to make further advances in the theory"--
