Angshul Majumdar ó 2 Summary
L 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 developmen.
Summary Compressed Sensing for Engineers
Compressed Sensing CS in theory deals with the problem of recovering a sparse signal from an under determined system of linear euations 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.
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Resonance Imaging making scans 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 reuires a basic understanding of signal processing and linear algebraCovers fundamenta.