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Kernel Mode Decomposition and the Programming of Kernels

Kernel Mode Decomposition and the Programming of Kernels

by Houman OwhadiClint Scovel and Gene Ryan Yoo
Paperback
Publication Date: 04/12/2021

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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 context of 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.


ISBN:
9783030821708
9783030821708
Category:
Differential calculus & equations
Format:
Paperback
Publication Date:
04-12-2021
Language:
English
Publisher:
Springer International Publishing AG
Country of origin:
Switzerland
Dimensions (mm):
235x155mm
Weight:
0.21kg

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