Analysis of Parameter Variability in Integrated Devices by Partial Least Squares Regression

Mourad Larbi, Riccardo Trinchero, Flavio G. Canavero, Philippe Besnier, Madhavan Swaminathan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

This paper focuses on the application of the partial least squares (PLS) regression to the uncertainty quantification of the responses of complex stochastic systems. It considers the development of a surrogate model using a limited set of training samples in order to estimate statistical quantities of the system output with relatively low computational cost compared to the standard brute force Monte Carlo (MC) simulation. The performance and the strength of the proposed modeling scheme is investigated for an integrated voltage regulator (IVR) with 8 random variables. The results highlight the ability of the PLS regression to deals with complex nonlinear problems with very few principal components, also providing important insights about the input variables.

Original languageEnglish (US)
Title of host publicationSPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728142043
DOIs
StatePublished - May 2020
Event24th IEEE Workshop On Signal and Power Integrity, SPI 2020 - Cologne, Germany
Duration: May 17 2020May 20 2020

Publication series

NameSPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings

Conference

Conference24th IEEE Workshop On Signal and Power Integrity, SPI 2020
Country/TerritoryGermany
CityCologne
Period5/17/205/20/20

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality

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