Compressed sensing for engineers

✍ Scribed by Majumdar, Angshul

Publisher: CRC Press
Year: 2019
Tongue: English
Leaves: 293
Series: Devices circuits and systems
Edition: First edition
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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

"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 the recent past, CS has helped reduce scan time in Magnetic Resonance Imaging (making scans more feasible for pediatric and geriatric subjects) and reduce the health hazard in X-Ray Computed CT. The book with be suitable for an engineering student in signal processing and requires a basic understanding of signal processing and linear algebra"--Provided by publisher Read more...

Abstract: 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

✦ Subjects

Compressed sensing (Telecommunication);Image processing;Digital techniques;Image compression;Signal processing;Mathematics;Image compression;Image processing;Digital techniques;Signal processing;Mathematics

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