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A hierarchical stochastic macromodeling approach is proposed for the efficient variability analysis of complex nonlinear electronic systems. A combination of the Transfer Function Trajectory and Polynomial Chaos methods is used to generate stochastic macromodels. In order to reduce the computational complexity of the model generation when the number of stochastic variables increases, a hierarchical...
A technique for automated generation of compact behavioural models is presented. The extracted models are capable of capturing highly nonlinear systems with good accuracy. The proposed technique is an extension to the well known trajectory-based piecewise models, where local expansions of the state trajectory are stitched together using weighting functions. This idea is combined with response surface...
This paper investigates the stopping criteria for Monte-Carlo (MC)-based yield optimization of analog integrated circuits. Available stopping criteria are briefly reviewed and a new adaptive criterion, called combined global and local improvement (ComImp) is presented. Experimental results show that the proposed stopping criterion has the following two advantages: (1) low risk of early termination...
In this paper a new methodology is proposed for automated generation of EMC-aware behavioral models. Tightening EMC regulations require elaborate testing and simulation of EMC susceptibility of analog circuits during the design stage. A classification strategy detects EMC-sensitive devices which allows us to incorporate a more elaborate device model when accuracy is needed due to rectification effects...
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