Numerically Stable Moment Matching for Linear Systems Parameterized by Polynomials in Multiple Variables With Applications to Finite Element Models of Microwave Structures

被引：9

作者：

Farle, Ortwin ^{[1
]}

Dyczij-Edlinger, Romanus ^{[1
]}

机构：

[1] Univ Saarland, Chair Electromagnet Theory, D-66123 Campus, Germany

来源：

IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION | 2010年 / 58卷 / 11期

关键词：

Reduced order systems; finite element methods; WAVE-FORM EVALUATION; ORDER REDUCTION; PADE-APPROXIMATION; CIRCUIT ANALYSIS; LANCZOS PROCESS; NETWORKS; SIMULATION; EQUATIONS; FREQUENCY; MATRIX;

D O I：

10.1109/TAP.2010.2071368

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Parametric model-order reduction is a very powerful methodology for analyzing large-scale systems with multiple parameters. This paper extends the theory of moment-matching single-point methods to linear systems parameterized by multivariate polynomials. We propose a new algorithm that exhibits high numerical robustness and short runtimes, allows for direction-dependent model orders, and is easy to parallelize. To demonstrate the accuracy and efficiency of the suggested approach, we present the response surfaces of two microwave finite-element models, featuring the operating frequency and material properties as parameters.

引用

页码：3675 / 3684

页数：10

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