Multi-objective sensitivity-based optimization of analog circuits exploiting NSGA-II front ranking

Pedro Miguel Ribeiro Pereira; Maria Helena Silva Fino; DEE Group Author

doi:10.1109/SMACD.2015.7301696

Multi-objective sensitivity-based optimization of analog circuits exploiting NSGA-II front ranking

Pedro Miguel Ribeiro Pereira, Maria Helena Silva Fino, DEE Group Author

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

4 Citations (Scopus)

Abstract

This work deals with the multi-objective optimization of analog circuits by generating the Pareto front where elements are low sensitive to parameters{\textquoteright} variations. NSGA-II is used for obtaining the non-dominated solutions. Richardson extrapolation technique is used for the in-loop optimization approach for computing partial derivatives and, thus, the solutions{\textquoteright} sensitivity. NSGA-II Pareto fronts{\textquoteright} intrinsic ranking is exploited for the generation of the new {\textquoteleft}low-sensitive{\textquoteright} Pareto front. The case of the optimal sizing of a CMOS voltage follower is considered to exemplify the proposed approach.

Original language	Unknown
Title of host publication	n/a
Place of Publication	Istanbul, Turkey
Pages	1-4
DOIs	https://doi.org/10.1109/SMACD.2015.7301696
Publication status	Published - 1 Jan 2015
Event	International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD) - Duration: 1 Jan 2015 → …

Conference

Conference	International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD)
Period	1/01/15 → …

Access to Document

10.1109/SMACD.2015.7301696

http://dx.doi.org/10.1109/SMACD.2015.7301696

Cite this

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title = "Multi-objective sensitivity-based optimization of analog circuits exploiting NSGA-II front ranking",

abstract = "This work deals with the multi-objective optimization of analog circuits by generating the Pareto front where elements are low sensitive to parameters{\textquoteright} variations. NSGA-II is used for obtaining the non-dominated solutions. Richardson extrapolation technique is used for the in-loop optimization approach for computing partial derivatives and, thus, the solutions{\textquoteright} sensitivity. NSGA-II Pareto fronts{\textquoteright} intrinsic ranking is exploited for the generation of the new {\textquoteleft}low-sensitive{\textquoteright} Pareto front. The case of the optimal sizing of a CMOS voltage follower is considered to exemplify the proposed approach.",

keywords = "statistics, sociology, optimization, analog circuits, sensitivity analysis, extrapolation",

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N2 - This work deals with the multi-objective optimization of analog circuits by generating the Pareto front where elements are low sensitive to parameters{\textquoteright} variations. NSGA-II is used for obtaining the non-dominated solutions. Richardson extrapolation technique is used for the in-loop optimization approach for computing partial derivatives and, thus, the solutions{\textquoteright} sensitivity. NSGA-II Pareto fronts{\textquoteright} intrinsic ranking is exploited for the generation of the new {\textquoteleft}low-sensitive{\textquoteright} Pareto front. The case of the optimal sizing of a CMOS voltage follower is considered to exemplify the proposed approach.

AB - This work deals with the multi-objective optimization of analog circuits by generating the Pareto front where elements are low sensitive to parameters{\textquoteright} variations. NSGA-II is used for obtaining the non-dominated solutions. Richardson extrapolation technique is used for the in-loop optimization approach for computing partial derivatives and, thus, the solutions{\textquoteright} sensitivity. NSGA-II Pareto fronts{\textquoteright} intrinsic ranking is exploited for the generation of the new {\textquoteleft}low-sensitive{\textquoteright} Pareto front. The case of the optimal sizing of a CMOS voltage follower is considered to exemplify the proposed approach.

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KW - sociology

KW - optimization

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KW - sensitivity analysis

KW - extrapolation

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