Fast Analysis and Optimization of Sparsely Distributed Partial Modification Problems-Reference-Cited by-同舟云学术

Fast Analysis and Optimization of Sparsely Distributed Partial Modification Problems

Published:2022-08 Issue:8 Volume:70 Page:3817-3826
ISSN:0018-9480
Container-title:IEEE Transactions on Microwave Theory and Techniques
language:
Short-container-title:IEEE Trans. Microwave Theory Techn.

Author:

Fang Xiaoxing¹^ORCID,Heldring Alexander²^ORCID,Rius Juan M.²^ORCID,Cao Qunsheng³^ORCID

Affiliation:

1. Research Center of Applied Electromagnetics, School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China

2. Department of Signal Processing and Telecommunications, CommSensLab, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain

3. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China

Funder

National Nature Science Foundation of China

China Scholarship Council

Startup Foundation for Introducing Talent of the Nanjing University of Information Science and Technology

Ministerio de Ciencia e Innovacion

Unidad de Excelencia Maria de Maeztu

Agencia Estatal de Investigación, Spain

Catalan Agency for Management of University and Research Grants (AGAUR) under Research Group

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiation

Link

http://xplorestaging.ieee.org/ielx7/22/9851481/09802861.pdf?arnumber=9802861

Reference24 articles.

1. Genetic algorithms and method of moments (GA/MOM) for the design of integrated antennas

2. Analysis of Partial Modifications on Electrically Large Bodies via Characteristic Basis Functions

3. A Butterfly-Based Direct Integral-Equation Solver Using Hierarchical LU Factorization for Analyzing Scattering From Electrically Large Conducting Objects

4. Multiscale Compressed Block Decomposition for Fast Direct Solution of Method of Moments Linear System

5. Multiscale Compressed and Spliced Sherman–Morrison–Woodbury Algorithm With Characteristic Basis Function Method

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