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Kernel Mode Decomposition and the Programming of Kernels
Engelsk Paperback
Kernel Mode Decomposition and the Programming of Kernels
Engelsk Paperback

669 kr
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Om denne bog

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.


Product detaljer
Sprog:
Engelsk
Sider:
118
ISBN-13:
9783030821708
Indbinding:
Paperback
Udgave:
ISBN-10:
3030821706
Udg. Dato:
4 dec 2021
Længde:
0mm
Bredde:
155mm
Højde:
235mm
Forlag:
Springer Nature Switzerland AG
Oplagsdato:
4 dec 2021
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