Compressed Sensing for Engineers

Nonfiction, Science & Nature, Technology, Electricity
Cover of the book Compressed Sensing for Engineers by Angshul Majumdar, CRC Press
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Author: Angshul Majumdar ISBN: 9781351261340
Publisher: CRC Press Publication: December 7, 2018
Imprint: CRC Press Language: English
Author: Angshul Majumdar
ISBN: 9781351261340
Publisher: CRC Press
Publication: December 7, 2018
Imprint: CRC Press
Language: English

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
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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.

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