State-of-the-Art: AI-Assisted Surrogate Modeling and Optimization for Microwave Filters

Yang Yu1; Zhen Zhang2; Qingsha S. Cheng3; Bo Liu4; Yi Wang1; Cheng Guo5; Terry Tao Ye3

2022

10.1109/TMTT.2022.3208898

IEEE Transactions on Microwave Theory and Techniques   影响因子和分区

1557-9670

Artificial intelligent (AI) computer-aided design (CAD) coupling matrix design knowledge electromagnetic (EM)-simulation based design machine learning microwave filters optimization sampling surrogate modeling

其他

ENGINEERING

IEEE

1.Electronic and System Engineering, School of Electrical, University of Birmingham, Birmingham, U.K.
2.School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China
3.Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China
4.James Watt School of Engineering, University of Glasgow, Glasgow, U.K.
5.Department of Information and Communication Engineering, Xi’an Jiaotong University, Xi’an, China

Yang Yu,Zhen Zhang,Qingsha S. Cheng,et al. State-of-the-Art: AI-Assisted Surrogate Modeling and Optimization for Microwave Filters[J]. IEEE Transactions on Microwave Theory and Techniques,2022,PP(99):1-17.

Yang Yu.,Zhen Zhang.,Qingsha S. Cheng.,Bo Liu.,Yi Wang.,...&Terry Tao Ye.(2022).State-of-the-Art: AI-Assisted Surrogate Modeling and Optimization for Microwave Filters.IEEE Transactions on Microwave Theory and Techniques,PP(99),1-17.

Yang Yu,et al."State-of-the-Art: AI-Assisted Surrogate Modeling and Optimization for Microwave Filters".IEEE Transactions on Microwave Theory and Techniques PP.99(2022):1-17.