Compressed Sensing Engineers by Majumdar Angshul (33 results)

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Paperback. Condition: new. Paperback. 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 The first portion of the book is on the algorithms. The second portion of the book is about applications, covering some of the major areas like computational imaging, medical imaging, biomedical signal processing and machine learning. The concentration of this book is on algorithms and applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Condition: new. Paperback. 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 The first portion of the book is on the algorithms. The second portion of the book is about applications, covering some of the major areas like computational imaging, medical imaging, biomedical signal processing and machine learning. The concentration of this book is on algorithms and applications. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Condition: New. 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 .

Paperback. Condition: new. Paperback. 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 The first portion of the book is on the algorithms. The second portion of the book is about applications, covering some of the major areas like computational imaging, medical imaging, biomedical signal processing and machine learning. The concentration of this book is on algorithms and applications. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Hardcover. Condition: new. Hardcover. 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 The first portion of the book is on the algorithms. The second portion of the book is about applications, covering some of the major areas like computational imaging, medical imaging, biomedical signal processing and machine learning. The concentration of this book is on algorithms and applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Hardcover. Condition: new. Hardcover. 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 The first portion of the book is on the algorithms. The second portion of the book is about applications, covering some of the major areas like computational imaging, medical imaging, biomedical signal processing and machine learning. The concentration of this book is on algorithms and applications. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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) andhas also helped reducethe health hazard in X-Ray Computed CT. This book is a valuable resourcesuitable 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 294 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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) andhas also helped reducethe health hazard in X-Ray Computed CT. This book is a valuable resourcesuitable 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.

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