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Data-Driven Parameterized Model Order Reduction Using z-Domain Multivariate Orthonormal Vector Fitting Technique

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Model Reduction for Circuit Simulation

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 74))

Abstract

Efficient real-time design space exploration, design optimization and sensitivity analysis call for Parameterized Model Order Reduction (PMOR) techniques to take into account several design parameters, such as geometrical layout or substrate characteristics, in addition to time or frequency. This chapter presents a robust multivariate extension of the z-domain Orthonormal Vector Fitting technique. The new method provides accurate and compact rational parametric macromodels based on numerical electromagnetic simulations or measurements in either frequency-domain or time-domain. The technique can be seen as a data-driven PMOR method.

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Notes

  1. 1.

    Momentum EEsof EDA, Agilent Technologies, Santa Rosa, CA.

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Acknowledgements

This work was supported by a grant of the Research Foundation-Flanders (FWO-Vlaanderen).

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Correspondence to Francesco Ferranti .

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Ferranti, F., Deschrijver, D., Knockaert, L., Dhaene, T. (2011). Data-Driven Parameterized Model Order Reduction Using z-Domain Multivariate Orthonormal Vector Fitting Technique. In: Benner, P., Hinze, M., ter Maten, E. (eds) Model Reduction for Circuit Simulation. Lecture Notes in Electrical Engineering, vol 74. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0089-5_7

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  • DOI: https://doi.org/10.1007/978-94-007-0089-5_7

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