首页    期刊浏览 2024年11月29日 星期五
登录注册

文章基本信息

  • 标题:Krylov Subspace Methods for Model Order Reduction in Computational Electromagnetics * * This work is partially supported by the CPDA144817 grant of the University of Padova.
  • 本地全文:下载
  • 作者:Matteo Bonotto ; Angelo Cenedese ; Paolo Bettini
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2017
  • 卷号:50
  • 期号:1
  • 页码:6355-6360
  • DOI:10.1016/j.ifacol.2017.08.1019
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper presents a model order reduction method via Krylov subspace projection, for applications in the field of computational electromagnetics (CEM). The approach results to be suitable both for SISO and MIMO systems, and is based on the numerically robust Arnoldi procedure. We have studied the model order reduction as the number of inputs and outputs changes, to better understand the behavior of the reduction technique. Relevant CEM examples related to the reduction of finite element method models are presented to validate this methodology, both in the 2D and in the 3D case.
  • 关键词:KeywordsModel order reduction (MOR)Krylov subspace methodArnoldi algorithmComputational Electromagnetics
国家哲学社会科学文献中心版权所有