Multi-Parameter Modeling with ANN for Antenna Design

被引：0

作者：

Wu, Zhuochun ^{[1
]}

Yang, Yang ^{[2
]}

Yao, Zhixin ^{[2
]}

机构：

[1] Univ Elect Sci & Technol China, Natl Key Lab & Technol Commun, Chengdu, Sichuan, Peoples R China

[2] Univ Elect Sci & Technol China, Sch Phys Elect, Chengdu, Sichuan, Peoples R China

来源：

2018 IEEE ANTENNAS AND PROPAGATION SOCIETY INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION & USNC/URSI NATIONAL RADIO SCIENCE MEETING | 2018年

关键词：

artificial neural network (ANN); data classification; pole-residue-based transfer function (TF); ultrawide band (UWB) antenna; ARTIFICIAL NEURAL-NETWORKS; COMPUTER-AIDED-DESIGN; MICROWAVE; COMPONENTS; RF;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, a novel artificial neural network (ANN) model with three parallel and independent branches is proposed. A data-classification technique is introduced to classify antenna geometrical variables into the proper categories. Once the geometrical variables are input, the ANN model can simultaneously obtain the antenna VSWR, gain and radiation pattern from each independent branch. The validity and efficiency of this proposed model are confirmed with an optimization design of an ultrawide band (UWB) antenna example.

引用

页码：2381 / 2382

页数：2

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