A stochastic collocation technique for time-domain variability analysis of active circuits

Kaimin Guo · Francesco Ferranti · Behzad Nouri · Michel S. Nakhla

8 citations0/0 files storedIEEE Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS)

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Probabilistic and Robust Engineering Design Low-power high-performance VLSI design Model Reduction and Neural Networks

Abstract

A novel method is presented for time-domain statistical analysis of large active circuits with multiple stochastic parameters. It is based on a stability-preserving model order reduction algorithm coupled with stochastic collocation schemes. Pertinent numerical results validate the proposed method.

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References

2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations 2005High-Order Collocation Methods for Differential Equations with Random Inputs 2007A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data 2008A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data 2012Multifidelity Uncertainty Quantification Using Non-Intrusive Polynomial Chaos and Stochastic Collocation 2011Stochastic Analysis of Multiconductor Cables and Interconnects 2015Generalized Decoupled Polynomial Chaos for Nonlinear Circuits With Many Random Parameters 2012Variability Analysis of Multiport Systems Via Polynomial-Chaos Expansion

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