Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits

Author

Zheng Zhang ; El-Moselhy, Tarek A. ; Maffezzoni, Paolo ; Elfadel, Ibrahim M. ; Daniel, Luca

Author_Institution

Massachusetts Inst. of Technol., Cambridge, MA, USA

Volume

60

Issue

10

fYear

2013

fDate

Oct. 2013

Firstpage

687

Lastpage

691

Abstract

This brief proposes an uncertainty quantification method for the periodic steady-state (PSS) analysis with both Gaussian and non-Gaussian variations. Our stochastic testing formulation for the PSS problem provides superior efficiency over both Monte Carlo methods and existing spectral methods. The numerical implementation of a stochastic shooting Newton solver is presented for both forced and autonomous circuits. Simulation results on some analog/RF circuits are reported to show the effectiveness of our proposed algorithms.

Keywords

Monte Carlo methods; analogue integrated circuits; radiofrequency integrated circuits; stochastic systems; Monte Carlo methods; PSS analysis; analog-RF circuits; autonomous circuits; forced circuits; nonGaussian variations; periodic steady state; stochastic shooting Newton solver; stochastic testing formulation; uncertainty quantification; Equations; Jacobian matrices; Mathematical model; Oscillators; Steady-state; Testing; Uncertainty; Circuit simulation; periodic steady state; stochastic testing (ST); uncertainty quantification (UQ);

fLanguage

English

Journal_Title

Circuits and Systems II: Express Briefs, IEEE Transactions on

Publisher

ieee

ISSN

1549-7747

Type

jour

DOI

10.1109/TCSII.2013.2278110

Filename

6588881