Simultaneous Step-Size and Path Control for Efficient Transient Noise Analysis

Noise in electronic components is a random phenomenon that can adversely affect the desired operation of a circuit. Transient noise analysis is designed to consider noise effects in circuit simulation. Taking noise into account by means of Gaussian white noise currents, mathematical modelling leads to stochastic differential algebraic equations (SDAEs) with a large number of small noise sources. Their simulation requires an efficient numerical time integration by mean-square convergent numerical methods. As efficient approaches for their integration we discuss adaptive linear multi-step methods, together with a new step-size and path selection control strategy. Numerical experiments on industrial real-life applications illustrate the theoretical findings.

[1]  Michael V. Tretyakov,et al.  Numerical methods for SDEs with small noise , 2004 .

[2]  Caren Tischendorf,et al.  Structural analysis of electric circuits and consequences for MNA , 2000, Int. J. Circuit Theory Appl..

[3]  Georg Denk,et al.  Modelling and simulation of transient noise in circuit simulation , 2007 .

[4]  Desmond J. Higham,et al.  An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations , 2001, SIAM Rev..

[5]  Renate Winkler,et al.  Adaptive Methods for Transient Noise Analysis , 2007 .

[6]  Evelyn Buckwar,et al.  Multistep methods for SDEs and their application to problems with small noise , 2006, SIAM J. Numer. Anal..

[7]  Thorsten Sickenberger,et al.  Local error estimates for moderately smooth problems: Part II—SDEs and SDAEs with small noise , 2009 .

[8]  Werner Römisch,et al.  Efficient transient noise analysis in circuit simulation , 2006 .

[9]  R. Winkler Stochastic differential algebraic equations of index 1 and applications in circuit simulation , 2003 .

[10]  Ewa Weinmüller,et al.  Local error estimates for moderately smooth problems: Part I – ODEs and DAEs , 2007 .

[11]  Thorsten Sickenberger,et al.  Mean-square convergence of stochastic multi-step methods with variable step-size , 2008 .

[12]  D. Williams STOCHASTIC DIFFERENTIAL EQUATIONS: THEORY AND APPLICATIONS , 1976 .

[13]  Werner Römisch,et al.  Stepsize Control for Mean-Square Numerical Methods for Stochastic Differential Equations with Small Noise , 2006, SIAM J. Sci. Comput..

[14]  Jitka Dupacová,et al.  Scenario reduction in stochastic programming , 2003, Math. Program..