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Variational Regularization of 3D Data: Experiments with MATLAB® (SpringerBriefs in Computer Science) - Tapa blanda
Sinopsis
Variational Regularization of 3D Data provides an introduction to variational methods for data modelling and its application in computer vision. In this book, the authors identify interpolation as an inverse problem that can be solved by Tikhonov regularization. The proposed solutions are generalizations of one-dimensional splines, applicable to n-dimensional data and the central idea is that these splines can be obtained by regularization theory using a trade-off between the fidelity of the data and smoothness properties.
As a foundation, the authors present a comprehensive guide to the necessary fundamentals of functional analysis and variational calculus, as well as splines. The implementation and numerical experiments are illustrated using MATLAB®. The book also includes the necessary theoretical background for approximation methods and some details of the computer implementation of the algorithms. A working knowledge of multivariable calculus and basic vector and matrix methods should serve as an adequate prerequisite.
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Reseña del editor
Variational Regularization of 3D Data provides an introduction to variational methods for data modelling and its application in computer vision. In this book, the authors identify interpolation as an inverse problem that can be solved by Tikhonov regularization. The proposed solutions are generalizations of one-dimensional splines, applicable to n-dimensional data and the central idea is that these splines can be obtained by regularization theory using a trade-off between the fidelity of the data and smoothness properties.
As a foundation, the authors present a comprehensive guide to the necessary fundamentals of functional analysis and variational calculus, as well as splines. The implementation and numerical experiments are illustrated using MATLAB®. The book also includes the necessary theoretical background for approximation methods and some details of the computer implementation of the algorithms. A working knowledge of multivariable calculus and basic vector and matrix methods should serve as an adequate prerequisite.
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- EditorialSpringer
- Año de publicación2014
- ISBN 10 1493905325
- ISBN 13 9781493905324
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas96
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Variational Regularization of 3D Data: Experiments with MATLAB® (SpringerBriefs in Computer Science)
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Variational Regularization of 3D Data
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Springer New York Mrz 2014, 2014
ISBN 10: 1493905325
ISBN 13: 9781493905324
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Variational Regularization of 3D Data provides an introduction to variational methods for data modelling and its application in computer vision. In this book, the authors identify interpolation as an inverse problem that can be solved by Tikhonov regularization. The proposed solutions are generalizations of one-dimensional splines, applicable to n-dimensional data and the central idea is that these splines can be obtained by regularization theory using a trade-off between the fidelity of the data and smoothness properties.As a foundation, the authors present a comprehensive guide to the necessary fundamentals of functional analysis and variational calculus, as well as splines. The implementation and numerical experiments are illustrated using MATLAB®. The book also includes the necessary theoretical background for approximation methods and some details of the computer implementation of the algorithms. A working knowledge of multivariable calculus and basic vector and matrix methods should serve as an adequate prerequisite. 96 pp. Englisch. Nº de ref. del artículo: 9781493905324
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Variational Regularization of 3D Data
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Springer New York, 2014
ISBN 10: 1493905325
ISBN 13: 9781493905324
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Includes supplementary material: sn.pub/extrasVariational Regularization of 3D Data provides an introduction to variational methods for data modelling and its application in computer vision. In this book, the authors identify interpolation as . Nº de ref. del artículo: 4213826
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Variational Regularization of 3D Data : Experiments with MATLAB®
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Variational Regularization of 3D Data provides an introduction to variational methods for data modelling and its application in computer vision. In this book, the authors identify interpolation as an inverse problem that can be solved by Tikhonov regularization. The proposed solutions are generalizations of one-dimensional splines, applicable to n-dimensional data and the central idea is that these splines can be obtained by regularization theory using a trade-off between the fidelity of the data and smoothness properties.As a foundation, the authors present a comprehensive guide to the necessary fundamentals of functional analysis and variational calculus, as well as splines. The implementation and numerical experiments are illustrated using MATLAB®. The book also includes the necessary theoretical background for approximation methods and some details of the computer implementation of the algorithms. A working knowledge of multivariable calculus and basic vector and matrix methods should serve as an adequate prerequisite. Nº de ref. del artículo: 9781493905324
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Variational Regularization of 3d Data : Experiments With Matlab
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Variational Regularization of 3D Data : Experiments with MATLAB
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Variational Regularization of 3D Data: Experiments with MATLAB (R)
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ISBN 13: 9781493905324
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Variational Regularization of 3d Data : Experiments With Matlab
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Montegranario:Variational Regularizatio (eng)
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Variational Regularization of 3D Data
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