arrow
返回

VECTOR FITTING FOR MATRIX-VALUED RATIONAL APPROXIMATION

delete2015-01-01
delete39
delete
OA
AI
D
Drmac, Z. *
G
Gugercin, S.
B
Beattie, C.
DOI:10.1137/15M1010774delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
Vector Fitting (VF) is a popular method of constructing rational approximants that provides a least squares fit to frequency response measurements. In an earlier work, we provided an analysis of VF for scalar-valued rational functions and established a connection with optimal H-2 approximation. We build on this work and extend the previous framework to include the construction of effective rational approximations to matrix-valued functions, a problem which presents significant challenges that do not appear in the scalar case. Transfer functions associated with multiinput/multioutput (MIMO) dynamical systems typify the class of functions that we consider here. Others have also considered extensions of VF to matrix-valued functions and related numerical implementations are readily available. However, to the best of our knowledge, a detailed analysis of numerical issues that arise does not yet exist. We offer such an analysis including critical implementation details here. One important issue that arises for VF on matrix-valued functions that has remained largely unaddressed is the control of the McMillan degree of the resulting rational approximant; the McMillan degree can grow very high in the case of large input/output dimensions. We introduce two new mechanisms for controlling the McMillan degree of the final approximant, one based on alternating least-squares minimization and one based on ancillary system-theoretic reduction methods. Motivated in part by our earlier work on the scalar VF problem as well as by recent innovations for computing optimal H2 approximation, we establish a connection with optimal H-2 approximation, and are able to improve significantly the fidelity of VF through numerical quadrature, with virtually no increase in cost or complexity. We provide several numerical examples to support the theoretical discussion and proposed algorithms.
Keyword:
least squares
frequency response
model order reduction
MIMO vector fitting
transfer function
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

SIAM Journal on Scientific Computing 封面图
SIAM Journal on Scientific Computing
IF:
2.6
论文数:
5.1K
被引数:
1.8W

机构

U
University of Zagreb
学者数:
1.8W
论文数: 1.3W
被引数: 1.1W
引用论文

引用论文

Time-Resolved In Situ Spectroscopy During Formation of the GaP/Si(100) Heterointerface
err2015-01-21
err0
PREAI
errOliver Supplie; Matthias M. May; Gabi Steinbach; Oleksandr Romanyuk; Frank Grosse; Andreas Nägelein; Peter Kleinschmidt; Sebastian Brückner; Thomas Hannappel
err分享
err收藏
err分享
err收藏
err分享
err收藏
A novel calix[4]arene-based dimeric-cholesteryl derivative: synthesis, gelation and unusual properties
err2015-01-01
err0
PREAI
errYing Wu; Kaiqiang Liu; Xiangli Chen; Yongping Chen; Shaofei Zhang; Junxia Peng; Yu Fang
err分享
err收藏
The genetic counseling profession in Austria: Stakeholders’ perspectives
err2021-04-02
err0
errOAAI
errGunda Schwaninger; Caroline Benjamin; Sabine Rudnik‐Schöneborn; Johannes Zschocke
err分享
err收藏
学者 查看更多内容