Kernel Mode Decomposition Programming by Owhadi Houman (17 results)
Language: English
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Published by Springer 2021-12-04, 2021
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Published by Springer, 2021
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Published by Springer, 2021
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Language: English
Published by Springer, 2021
Series: Book 9 of 9 - Surveys and Tutorials in the Applied Mathematical Sciences
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Published by Springer Nature, 2021
Series: Book 9 of 9 - Surveys and Tutorials in the Applied Mathematical Sciences
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Paperback. Condition: Brand New. 128 pages. 9.25x6.10x0.28 inches. In Stock.
Language: English
Published by Springer, Berlin|Springer International Publishing|Springer, 2021
Series: Book 9 of 9 - Surveys and Tutorials in the Applied Mathematical Sciences
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Condition: New. This monograph demonstrates a new approach to the classical mode decomposition problem through nonlinear regression models, which achieve near-machine precision in the recovery of the modes.This monograph demonstrates a new approach to the classical .
Language: English
Published by Springer, 2021
Series: Book 9 of 9 - Surveys and Tutorials in the Applied Mathematical Sciences
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Taschenbuch. Condition: Neu. Kernel Mode Decomposition and the Programming of Kernels | Houman Owhadi (u. a.) | Taschenbuch | Surveys and Tutorials in the Applied Mathematical Sciences | x | Englisch | 2021 | Springer | EAN 9783030821708 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelbe…rg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Language: English
Published by Springer, 2021
Series: Book 9 of 9 - Surveys and Tutorials in the Applied Mathematical Sciences
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Language: English
Published by Springer International Publishing Dez 2021, 2021
Series: Book 9 of 9 - Surveys and Tutorials in the Applied Mathematical Sciences
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This monograph demonstrates a new approach to the classical mode decomposition problem through nonlinear regression models, which achieve near-machine precision in the recovery of the modes. The presentation includes a review of gen…eralized additive models, additive kernels/Gaussian processes, generalized Tikhonov regularization, empirical mode decomposition, and Synchrosqueezing, which are all related to and generalizable under the proposed framework.Although kernel methods have strong theoretical foundations, they require the prior selection of a good kernel. While the usual approach to this kernel selection problem is hyperparameter tuning, the objective of this monograph is to present an alternative (programming) approach to the kernel selection problem while using mode decomposition as a prototypical pattern recognition problem. In this approach, kernels are programmed for the task at hand through the programming of interpretable regression networks in the contextof additive Gaussian processes.It is suitable for engineers, computer scientists, mathematicians, and students in these fields working on kernel methods, pattern recognition, and mode decomposition problems. 128 pp. Englisch.
Language: English
Published by Springer, 2021
Series: Book 9 of 9 - Surveys and Tutorials in the Applied Mathematical Sciences
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Language: English
Published by Springer, 2021
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Language: English
Published by Springer, Palgrave Macmillan Dez 2021, 2021
Series: Book 9 of 9 - Surveys and Tutorials in the Applied Mathematical Sciences
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This monograph demonstrates a new approach to the classical mode decomposition problem through nonlinear regression models, which achieve near-machine precision in the recovery of the modes. The presentation includes a review of general…ized additive models, additive kernels/Gaussian processes, generalized Tikhonov regularization, empirical mode decomposition, and Synchrosqueezing, which are all related to and generalizable under the proposed framework.Although kernel methods have strong theoretical foundations, they require the prior selection of a good kernel. While the usual approach to this kernel selection problem is hyperparameter tuning, the objective of this monograph is to present an alternative (programming) approach to the kernel selection problem while using mode decomposition as a prototypical pattern recognition problem. In this approach, kernels are programmed for the task at hand through the programming of interpretable regression networks in the contextof additive Gaussian processes.It is suitable for engineers, computer scientists, mathematicians, and students in these fields working on kernel methods, pattern recognition, and mode decomposition problems.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 128 pp. Englisch.
