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Journal of Electromagnetic Waves and Applications Volume 22, 2008 - Issue 1
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Articles

Mim Capacitor Modeling by Support Vector Regression

Z. Q. Yang Microwave Center, University of Electronic Science and Technology of China, Chengdu 610054, China
,
T. Yang Microwave Center, University of Electronic Science and Technology of China, Chengdu 610054, China
,
Y. Liu Microwave Center, University of Electronic Science and Technology of China, Chengdu 610054, China
&
S. H. Han Microwave Center, University of Electronic Science and Technology of China, Chengdu 610054, China
Pages 61-67 | Published online: 03 Apr 2012
 
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Abstract

The support vector regression (SVR) method is introduced to model the MIM capacitor in this paper. SVM is a type of learning machine based on the statistical learning theory, which implements the structural risk minimization principle to obtain a good generalization from limited size data sets. The SVR model of the MIM capacitor is trained and tested by using the data generated from EM simulation. Once the model is constructed, it can provides results approaching the accuracy of the EM simulated results without increasing the analysis time significantly, which proves the validity of the method.

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