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Aggiungi al carrelloCondizione: 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 .
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Editore: Taylor & Francis Ltd, London, 2022
ISBN 10: 1032338717 ISBN 13: 9781032338712
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Aggiungi al carrelloPaperback. Condizione: 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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Editore: Taylor & Francis Ltd, London, 2022
ISBN 10: 1032338717 ISBN 13: 9781032338712
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EUR 90,19
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Aggiungi al carrelloPaperback. Condizione: 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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Editore: Taylor & Francis Ltd, London, 2022
ISBN 10: 1032338717 ISBN 13: 9781032338712
Lingua: Inglese
Da: Grand Eagle Retail, Mason, OH, U.S.A.
EUR 87,90
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Aggiungi al carrelloPaperback. Condizione: 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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Editore: Taylor & Francis Inc, Bosa Roca, 2018
ISBN 10: 081536556X ISBN 13: 9780815365563
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EUR 195,88
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Aggiungi al carrelloHardcover. Condizione: 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.
Editore: Taylor & Francis Inc, Bosa Roca, 2018
ISBN 10: 081536556X ISBN 13: 9780815365563
Lingua: Inglese
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 288,66
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Aggiungi al carrelloHardcover. Condizione: 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.
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 72,00
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Aggiungi al carrelloTaschenbuch. Condizione: 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.
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Aggiungi al carrelloTaschenbuch. Condizione: 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.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 161,54
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Da: moluna, Greven, Germania
EUR 179,01
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 .