| 書目名稱 | Kernel Mode Decomposition and the Programming of Kernels |
| 編輯 | Houman Owhadi,Clint Scovel,Gene Ryan Yoo |
| 視頻video | http://file.papertrans.cn/543/542452/542452.mp4 |
| 概述 | Introduces programmable and interpretable regression networks for pattern recognition.Uses the classical mode decomposition problem to precisely illustrate models.Demonstrates a program for representi |
| 叢書名稱 | Surveys and Tutorials in the Applied Mathematical Sciences |
| 圖書封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2021 |
| 關(guān)鍵詞 | Kernel methods; empirical mode decomposition; Gaussian process regression; additive models; time-frequen |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-82171-5 |
| isbn_softcover | 978-3-030-82170-8 |
| isbn_ebook | 978-3-030-82171-5Series ISSN 2199-4765 Series E-ISSN 2199-4773 |
| issn_series | 2199-4765 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手機(jī)版|小黑屋|
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