Compressed Sensing for Engineers

AvAngshul Majumdar

Inbunden, Engelska, 2018

Del i serien Devices, Circuits, and Systems

2 300 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Fler format och utgåvor

Häftad

838 kr

Skickas inom 10-15 vardagar

Beskrivning

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 sensingMakes subject matter accessible for engineers of various levelsFocuses on algorithms including group-sparsity and row-sparsity, as well as applications to computational imaging, medical imaging, biomedical signal processing, and machine learningIncludes MATLAB examples for further development

Produktinformation

Utgivningsdatum:2018-12-03
Mått:156 x 234 x 22 mm
Vikt:560 g
Format:Inbunden
Språk:Engelska
Serie:Devices, Circuits, and Systems
Antal sidor:268
Förlag:Taylor & Francis Inc
ISBN:9780815365563

Utforska kategorier

Elektronik och kommunikationer inom Naturvetenskap och teknik

Mer om författaren

Angshul Majumdar is currently an assistant professor in Electronics and Communications Engineering at the Indraprastha Institute of Information Technology, Delhi (IIIT-D). He completed his PhD in 2012 from the University of British Columbia, Canada. His main contribution is in reducing acquisition time for Magnetic Resonance Imaging acquisition. He has around 25 papers on this topic published in top-tier journals and conferences. Angshul also works in other areas of biomedical imaging and signal processing. Previously, he was interested in the problem of classification and has published several papers on robust classification techniques with applications in face recognition, fingerprint recognition and optical character recognition. In all, Angshul has published over 50 papers in top-tier journals and conferences in the last 5 years. Before Angshul started in the academia, he worked in business consulting at the Pricewaterhouse Coopers.

Innehållsförteckning

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.