Research


Model Order Reduction using SPICE Simulation Traces

 
Paul Winkler , Henda Aridhi, Mohammed Zaki Hussein and Sofiene Tahar

The generation of fast models for device level circuit descriptions is a very active area of research. Model order reduction is an attractive technique for reducing the computational cost of dynamical models simulation. In this work, we propose an approach based on clustering, curve-fitting, linearization and Krylov space projection to build reduced models for nonlinear analog circuits. We demonstrate our model order reduction method for three nonlinear circuits: a voltage controlled oscillator, an operational amplifier and a digital frequency divider. Our experimental results show that the reduced models lead to an improvement in simulation speed while providing the same behavior of the original circuit design.



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Concordia University