Automatic Coupler Design Based on Artificial Neural Network With Self-Adaptive Local Surrogates-Reference-Cited by-同舟云学术

Automatic Coupler Design Based on Artificial Neural Network With Self-Adaptive Local Surrogates

Published:2022-11 Issue:11 Volume:70 Page:4711-4725
ISSN:0018-9480
Container-title:IEEE Transactions on Microwave Theory and Techniques
language:
Short-container-title:IEEE Trans. Microwave Theory Techn.

Author:

Liu Anlan¹^ORCID,Leng Maoheng²^ORCID,Pan Guangyuan³^ORCID,Yu Ming²^ORCID

Affiliation:

1. Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR

2. Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of EM Information, Southern University of Science and Technology, Shenzhen, China

3. Department of Automation and Electrical Engineering, Linyi University, Linyi, China

Funder

Shenzhen Key Laboratory of Electromagnetic (EM) Information

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiation

Link

http://xplorestaging.ieee.org/ielx7/22/9939118/09829227.pdf?arnumber=9829227

Reference37 articles.

1. An Efficient Method for Complex Antenna Design Based on a Self Adaptive Surrogate Model-Assisted Optimization Technique

2. Efficient Global Optimization of MEMS Based on Surrogate Model Assisted Evolutionary Algorithm

3. Use of a quasi-Newton method in a feedforward neural network construction algorithm

4. Single- and multiobjective evolutionary optimization assisted by Gaussian random field metamodels

5. Design of Compact Directional Couplers for UWB Applications

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