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ISBN 10: 365976213X ISBN 13: 9783659762130
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Published by LAP LAMBERT Academic Publishing, 2015
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Taschenbuch. Condition: Neu. Sparse Signal Processing and Compressed Sensing Recovery | Sujit Kumar Sahoo (u. a.) | Taschenbuch | 136 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659762130 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.
Language: English
Published by LAP LAMBERT Academic Publishing, 2015
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Published by LAP LAMBERT Academic Publishing Jul 2015, 2015
ISBN 10: 365976213X ISBN 13: 9783659762130
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The presented work revolves around sparsity. It contributes to dictionary training for sparse representation with a new algorithm and analysis. It showcases the usability of trained dictionary in image processing problems. It demonstrates a new framework for image recovery (inpainting and denoising) using sparse representation. In the end, it proposes an extension of the well-known sparse signal recovery algorithm, Orthogonal Matching Pursuit (OMP) for compressed sensing. It also provides a complete analysis of the proposed extension, and its theoretical guarantees. 136 pp. Englisch.
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Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 365976213X ISBN 13: 9783659762130
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sahoo Sujit KumarSujit Kumar Sahoo received the B.Tech. degree in electrical engineering in 2006 from NIT, Rourkela, India, and the Ph.D. degrees in electrical and electronic engineering in 2014 from NTU, Singapore. From 2006 to 2007.
Language: English
Published by LAP LAMBERT Academic Publishing Jul 2015, 2015
ISBN 10: 365976213X ISBN 13: 9783659762130
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The presented work revolves around sparsity. It contributes to dictionary training for sparse representation with a new algorithm and analysis. It showcases the usability of trained dictionary in image processing problems. It demonstrates a new framework for image recovery (inpainting and denoising) using sparse representation. In the end, it proposes an extension of the well-known sparse signal recovery algorithm, Orthogonal Matching Pursuit (OMP) for compressed sensing. It also provides a complete analysis of the proposed extension, and its theoretical guarantees.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 136 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 365976213X ISBN 13: 9783659762130
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The presented work revolves around sparsity. It contributes to dictionary training for sparse representation with a new algorithm and analysis. It showcases the usability of trained dictionary in image processing problems. It demonstrates a new framework for image recovery (inpainting and denoising) using sparse representation. In the end, it proposes an extension of the well-known sparse signal recovery algorithm, Orthogonal Matching Pursuit (OMP) for compressed sensing. It also provides a complete analysis of the proposed extension, and its theoretical guarantees.