Dekorationsartikel gehören nicht zum Leistungsumfang.
Kernel Mode Decomposition and the Programming of Kernels
Taschenbuch von Houman Owhadi (u. a.)
Sprache: Englisch

70,70 €*

inkl. MwSt.

Versandkostenfrei per Post / DHL

Lieferzeit 4-7 Werktage

Kategorien:
Beschreibung
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 generalized 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.
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 generalized 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.
Zusammenfassung

Introduces programmable and interpretable regression networks for pattern recognition

Uses the classical mode decomposition problem to precisely illustrate models

Demonstrates a program for representing nonlinearities through hierarchies

Inhaltsverzeichnis
Introduction.- Review.- The mode decomposition problem.- Kernel mode decomposition networks (KMDNets).- Additional programming modules and squeezing.- Non-trigonometric waveform and iterated KMD.- Unknown base waveforms.- Crossing frequencies, vanishing modes, and noise.- Appendix.
Details
Erscheinungsjahr: 2021
Fachbereich: Allgemeines
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 128
Reihe: Surveys and Tutorials in the Applied Mathematical Sciences
Inhalt: x
118 S.
10 s/w Illustr.
31 farbige Illustr.
118 p. 41 illus.
31 illus. in color.
ISBN-13: 9783030821708
ISBN-10: 3030821706
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Owhadi, Houman
Yoo, Gene Ryan
Scovel, Clint
Auflage: 1st ed. 2021
Hersteller: Springer International Publishing
Springer International Publishing AG
Surveys and Tutorials in the Applied Mathematical Sciences
Maße: 235 x 155 x 8 mm
Von/Mit: Houman Owhadi (u. a.)
Erscheinungsdatum: 04.12.2021
Gewicht: 0,207 kg
preigu-id: 120285973
Zusammenfassung

Introduces programmable and interpretable regression networks for pattern recognition

Uses the classical mode decomposition problem to precisely illustrate models

Demonstrates a program for representing nonlinearities through hierarchies

Inhaltsverzeichnis
Introduction.- Review.- The mode decomposition problem.- Kernel mode decomposition networks (KMDNets).- Additional programming modules and squeezing.- Non-trigonometric waveform and iterated KMD.- Unknown base waveforms.- Crossing frequencies, vanishing modes, and noise.- Appendix.
Details
Erscheinungsjahr: 2021
Fachbereich: Allgemeines
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 128
Reihe: Surveys and Tutorials in the Applied Mathematical Sciences
Inhalt: x
118 S.
10 s/w Illustr.
31 farbige Illustr.
118 p. 41 illus.
31 illus. in color.
ISBN-13: 9783030821708
ISBN-10: 3030821706
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Owhadi, Houman
Yoo, Gene Ryan
Scovel, Clint
Auflage: 1st ed. 2021
Hersteller: Springer International Publishing
Springer International Publishing AG
Surveys and Tutorials in the Applied Mathematical Sciences
Maße: 235 x 155 x 8 mm
Von/Mit: Houman Owhadi (u. a.)
Erscheinungsdatum: 04.12.2021
Gewicht: 0,207 kg
preigu-id: 120285973
Warnhinweis

Ähnliche Produkte

Ähnliche Produkte