Compressed Sensing PDF Download
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Author | : Simon Foucart |
Publisher | : Springer Science & Business Media |
Total Pages | : 634 |
Release | : 2013-08-13 |
Genre | : Computers |
ISBN | : 0817649484 |
Download A Mathematical Introduction to Compressive Sensing Book 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.
Author | : Antonio De Maio |
Publisher | : Cambridge University Press |
Total Pages | : 381 |
Release | : 2019-10-17 |
Genre | : Technology & Engineering |
ISBN | : 110857694X |
Download Compressed Sensing in Radar Signal Processing Book in PDF, ePub and Kindle
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 | : Steven L. Brunton |
Publisher | : Cambridge University Press |
Total Pages | : 615 |
Release | : 2022-05-05 |
Genre | : Computers |
ISBN | : 1009098489 |
Download Data-Driven Science and Engineering Book in PDF, ePub and Kindle
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Author | : M. Vidyasagar |
Publisher | : SIAM |
Total Pages | : 341 |
Release | : 2019-12-03 |
Genre | : Technology & Engineering |
ISBN | : 161197612X |
Download An Introduction to Compressed Sensing Book 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.
Author | : Avishy Y. Carmi |
Publisher | : Springer Science & Business Media |
Total Pages | : 505 |
Release | : 2013-09-13 |
Genre | : Technology & Engineering |
ISBN | : 364238398X |
Download Compressed Sensing & Sparse Filtering Book 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.
Author | : Vishal M. Patel |
Publisher | : Springer Science & Business Media |
Total Pages | : 111 |
Release | : 2013-02-11 |
Genre | : Technology & Engineering |
ISBN | : 1461463815 |
Download Sparse Representations and Compressive Sensing for Imaging and Vision Book in PDF, ePub and Kindle
Compressed sensing or compressive sensing is a new concept in signal processing where one measures a small number of non-adaptive linear combinations of the signal. These measurements are usually much smaller than the number of samples that define the signal. From these small numbers of measurements, the signal is then reconstructed by non-linear procedure. Compressed sensing has recently emerged as a powerful tool for efficiently processing data in non-traditional ways. In this book, we highlight some of the key mathematical insights underlying sparse representation and compressed sensing and illustrate the role of these theories in classical vision, imaging and biometrics problems.
Author | : Bhabesh Deka |
Publisher | : Springer |
Total Pages | : 122 |
Release | : 2018-12-29 |
Genre | : Technology & Engineering |
ISBN | : 9811335974 |
Download Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms Book in PDF, ePub and Kindle
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.
Author | : Yonina C. Eldar |
Publisher | : Cambridge University Press |
Total Pages | : 557 |
Release | : 2012-05-17 |
Genre | : Technology & Engineering |
ISBN | : 1107394392 |
Download Compressed Sensing Book in PDF, ePub and Kindle
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.
Author | : Yonina C. Eldar |
Publisher | : Cambridge University Press |
Total Pages | : 557 |
Release | : 2012-05-17 |
Genre | : Mathematics |
ISBN | : 1107005582 |
Download Compressed Sensing Book in PDF, ePub and Kindle
A detailed presentation of compressed sensing by leading researchers, covering the most significant theoretical and application-oriented advances.
Author | : Mahdi Khosravy |
Publisher | : Academic Press |
Total Pages | : 308 |
Release | : 2020-05-18 |
Genre | : Technology & Engineering |
ISBN | : 0128212489 |
Download Compressive Sensing in Healthcare Book in PDF, ePub and Kindle
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