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

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

doi:10.1109/SPI48784.2020.9218175

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

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

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 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 language	English (US)
Title of host publication	SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728142043
DOIs	https://doi.org/10.1109/SPI48784.2020.9218175
State	Published - May 2020
Event	24th IEEE Workshop On Signal and Power Integrity, SPI 2020 - Cologne, Germany Duration: May 17 2020 → May 20 2020

Publication series

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

Conference

Conference	24th IEEE Workshop On Signal and Power Integrity, SPI 2020
Country/Territory	Germany
City	Cologne
Period	5/17/20 → 5/20/20

All Science Journal Classification (ASJC) codes

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

Access to Document

10.1109/SPI48784.2020.9218175

Cite this

Larbi, M., Trinchero, R., Canavero, F. G., Besnier, P., & Swaminathan, M. (2020). Analysis of Parameter Variability in Integrated Devices by Partial Least Squares Regression. In SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings Article 9218175 (SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPI48784.2020.9218175

Larbi, Mourad ; Trinchero, Riccardo ; Canavero, Flavio G. et al. / Analysis of Parameter Variability in Integrated Devices by Partial Least Squares Regression. SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. (SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings).

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title = "Analysis of Parameter Variability in Integrated Devices by Partial Least Squares Regression",

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.",

author = "Mourad Larbi and Riccardo Trinchero and Canavero, {Flavio G.} and Philippe Besnier and Madhavan Swaminathan",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 24th IEEE Workshop On Signal and Power Integrity, SPI 2020 ; Conference date: 17-05-2020 Through 20-05-2020",

year = "2020",

month = may,

doi = "10.1109/SPI48784.2020.9218175",

language = "English (US)",

series = "SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings",

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Larbi, M, Trinchero, R, Canavero, FG, Besnier, P & Swaminathan, M 2020, Analysis of Parameter Variability in Integrated Devices by Partial Least Squares Regression. in SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings., 9218175, SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings, Institute of Electrical and Electronics Engineers Inc., 24th IEEE Workshop On Signal and Power Integrity, SPI 2020, Cologne, Germany, 5/17/20. https://doi.org/10.1109/SPI48784.2020.9218175

Analysis of Parameter Variability in Integrated Devices by Partial Least Squares Regression. / Larbi, Mourad; Trinchero, Riccardo; Canavero, Flavio G. et al.
SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. 9218175 (SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Analysis of Parameter Variability in Integrated Devices by Partial Least Squares Regression

AU - Larbi, Mourad

AU - Trinchero, Riccardo

AU - Canavero, Flavio G.

AU - Besnier, Philippe

AU - Swaminathan, Madhavan

PY - 2020/5

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N2 - 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.

AB - 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.

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M3 - Conference contribution

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Larbi M, Trinchero R, Canavero FG, Besnier P, Swaminathan M. Analysis of Parameter Variability in Integrated Devices by Partial Least Squares Regression. In SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. 9218175. (SPI 2020 - 24th IEEE Workshop On Signal and Power Integrity, Proceedings). doi: 10.1109/SPI48784.2020.9218175

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

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