Using Sensitivities for Symbolic Analysis and Model Order Reduction of Systems with Parameter Variation

  • Christian Salzig
  • Matthias Hauser
  • Alberto Venturi
Conference paper
Part of the Mathematics in Industry book series (MATHINDUSTRY, volume 17)

Abstract

The ongoing trend from micro- to nanoelectronics causes the growth of the relative parameter variation during the integrated electronic circuits production resulting in a consequent reduction of the production yield. Thus, symbolic model order reduction (MOR) techniques which were developed for design and analysis of nominal systems have to be adapted to assist the design of circuits which are robust with respect to parameter variation. Therefore, new sensitivity based methods have to be introduced to estimate the output of statistical systems and to improve the performance of the statistical MOR methods.

Keywords

Monte Carlo Simulation Parameter Variation Model Order Reduction Output Distribution Symbolic Model 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Christian Salzig
    • 1
  • Matthias Hauser
    • 1
  • Alberto Venturi
    • 1
  1. 1.Fraunhofer Institute for Industrial Mathematics ITWMKaiserslauternGermany

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