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EnglishThis paper presents a preliminary version of a probabilistic model for the uncertainty quantification of complex electronic systems resulting from the combination of the least-squares support vector machine (LS-SVM) and the Gaussian process (GP) regression. The proposed model, trained with a limited set of training pairs provided by a set of full-wave expensive simulations, is adopted for the prediction of the efficiency of an integrated voltage regulator (IVR) with 8 uniformly distributed random parameters. The accuracy and the feasibility of the proposed model have been investigated by comparing the model predictions and its confidence intervals with the results of a Monte Carlo (MC) full-wave simulation of the device.
Statistical Analysis of the Efficiency of an Integrated Voltage Regulator by means of a Machine Learning Model Coupled with Kriging Regression / Trinchero, R.; Larbi, M.; Swaminathan, Madhavan; Canavero, F. G.. - ELETTRONICO. - (2019), pp. 1-4. ((Intervento presentato al convegno 23rd IEEE Workshop on Signal and Power Integrity, SPI 2019 tenutosi a Chambéry, France, France nel 18-21 June 2019 [10.1109/SaPIW.2019.8781659].
| Titolo: | Statistical Analysis of the Efficiency of an Integrated Voltage Regulator by means of a Machine Learning Model Coupled with Kriging Regression | |
| Autori: | ||
| Data di pubblicazione: | 2019 | |
| Abstract: | This paper presents a preliminary version of a probabilistic model for the uncertainty quantifica...tion of complex electronic systems resulting from the combination of the least-squares support vector machine (LS-SVM) and the Gaussian process (GP) regression. The proposed model, trained with a limited set of training pairs provided by a set of full-wave expensive simulations, is adopted for the prediction of the efficiency of an integrated voltage regulator (IVR) with 8 uniformly distributed random parameters. The accuracy and the feasibility of the proposed model have been investigated by comparing the model predictions and its confidence intervals with the results of a Monte Carlo (MC) full-wave simulation of the device. | |
| ISBN: | 978-1-5386-8342-2 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| PID5867997.pdf | submitted paper | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
| Trinchero-Statistical.pdf | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
http://hdl.handle.net/11583/2768138
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