Nonlinear Signal Processing Based on Reproducing Kernel Hilbert Space: Concepts,Methods and Experiments - Softcover
Synopsis
Over the last few decades, there has been much research on reproducing kernel Hilbert space (RKHS) for machine learning. This monograph applies RKHS for nonlinear signal processing. It proposes a new statistical descriptor, called correntropy, to characterize the higher order statistical information and nonlinearity intrinsic to random processes. Correntropy and centered correntropy functions can be formulated as "generalized" correlation and covariance functions on nonlinearly transformed random signals via the data independent kernel functions. Those nonlinearly transformed signals appear on the sphere in the reproducing kernel Hilbert space induced by the kernel functions if isotropic kernel functions are used. The book offers new insights into the application of RKHS in nonlinear signal processing. Graduate students, professionals and researchers who are working on nonlinear signal processing and machine learning will find insightful information from the book.
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About the Author
Jianwu Xu received Ph.D. in Electrical and Computer Engineering from the University of Florida. Currently, He is a Post-Doctoral Scholar at the University of Chicago working on Computer-Aided Diagnosis.
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Nonlinear Signal Processing Based on Reproducing Kernel Hilbert Space
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LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838313089
ISBN 13: 9783838313085
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Over the last few decades, there has been much research on reproducing kernel Hilbert space (RKHS) for machine learning. This monograph applies RKHS for nonlinear signal processing. It proposes a new statistical descriptor, called correntropy, to characterize the higher order statistical information and nonlinearity intrinsic to random processes. Correntropy and centered correntropy functions can be formulated as 'generalized' correlation and covariance functions on nonlinearly transformed random signals via the data independent kernel functions. Those nonlinearly transformed signals appear on the sphere in the reproducing kernel Hilbert space induced by the kernel functions if isotropic kernel functions are used. The book offers new insights into the application of RKHS in nonlinear signal processing. Graduate students, professionals and researchers who are working on nonlinear signal processing and machine learning will find insightful information from the book. 164 pp. Englisch. Seller Inventory # 9783838313085
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Nonlinear Signal Processing Based on Reproducing Kernel Hilbert Space
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Xu JianwuJianwu Xu received Ph.D. in Electrical and Computer Engineeringfrom the University of Florida. Currently, He is a Post-DoctoralScholar at the University of Chicago working on Computer-AidedDiagnosis.Over the last few dec. Seller Inventory # 5412003
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Nonlinear Signal Processing Based on Reproducing Kernel Hilbert Space | Concepts,Methods and Experiments
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ISBN 13: 9783838313085
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Taschenbuch. Condition: Neu. Nonlinear Signal Processing Based on Reproducing Kernel Hilbert Space | Concepts,Methods and Experiments | Jianwu Xu | Taschenbuch | 164 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838313085 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 101493647
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Nonlinear Signal Processing Based on Reproducing Kernel Hilbert Space
Published by
LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838313089
ISBN 13: 9783838313085
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Over the last few decades, there has been much research on reproducing kernel Hilbert space (RKHS) for machine learning. This monograph applies RKHS for nonlinear signal processing. It proposes a new statistical descriptor, called correntropy, to characterize the higher order statistical information and nonlinearity intrinsic to random processes. Correntropy and centered correntropy functions can be formulated as 'generalized' correlation and covariance functions on nonlinearly transformed random signals via the data independent kernel functions. Those nonlinearly transformed signals appear on the sphere in the reproducing kernel Hilbert space induced by the kernel functions if isotropic kernel functions are used. The book offers new insights into the application of RKHS in nonlinear signal processing. Graduate students, professionals and researchers who are working on nonlinear signal processing and machine learning will find insightful information from the book.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 164 pp. Englisch. Seller Inventory # 9783838313085
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Nonlinear Signal Processing Based on Reproducing Kernel Hilbert Space : Concepts,Methods and Experiments
Published by
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838313089
ISBN 13: 9783838313085
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Over the last few decades, there has been much research on reproducing kernel Hilbert space (RKHS) for machine learning. This monograph applies RKHS for nonlinear signal processing. It proposes a new statistical descriptor, called correntropy, to characterize the higher order statistical information and nonlinearity intrinsic to random processes. Correntropy and centered correntropy functions can be formulated as 'generalized' correlation and covariance functions on nonlinearly transformed random signals via the data independent kernel functions. Those nonlinearly transformed signals appear on the sphere in the reproducing kernel Hilbert space induced by the kernel functions if isotropic kernel functions are used. The book offers new insights into the application of RKHS in nonlinear signal processing. Graduate students, professionals and researchers who are working on nonlinear signal processing and machine learning will find insightful information from the book. Seller Inventory # 9783838313085
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Nonlinear Signal Processing Based on Reproducing Kernel Hilbert Space: Concepts,Methods and Experiments
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