Majumdar A Compressed Sensing for Engineers 2019 torrent

Textbook in PDF format

Compressed Sensing (CS) in theory deals with the problem of recovering a sparse signal from an under-determined system of linear equations. The topic is of immense practical significance since all naturally occurring signals can be sparsely represented in some domain. In recent years, CS has helped reduce scan time in Magnetic Resonance Imaging (making scans more feasible for pediatric and geriatric subjects) and has also helped reduce the health hazard in X-Ray Computed CT. This book is a valuable resource suitable for an engineering student in signal processing and requires a basic understanding of signal processing and linear algebra.
Covers fundamental concepts of compressed sensing
Makes subject matter accessible for engineers of various levels
Focuses on algorithms including group-sparsity and row-sparsity, as well as applications to computational imaging, medical imaging, biomedical signal processing, and machine learning
Includes MATLAB examples for further development
Introduction
Greedy Algorithms
Sparse Recovery
Co-sparse Recovery
Group Sparsity
Joint Sparsity
Low-Rank Matrix Recovery
Combined Sparse and Low-Rank Recovery
Dictionary Learning
Medical Imaging
Biomedical Signal Reconstruction
Regression
Classification
Computational Imaging
Denoising