Multi-Objective Intelligent Optimization Design Method of Microstrip Antenna Based on Back Propagation Neural Network

被引：0
作者：
Liu, Dingli [1 ]
Yang, Yue [1 ]
Xu, Guilin [2 ]
Yu, Xian [1 ]
机构：
[1] Guangxi Nat Resources Vocat & Tech Coll, Nanning 532199, Guangxi, Peoples R China
[2] Nanning Normal Univ, Key Lab Environm Change & Resources Use Beibu Gulf, Minist Educ, Nanning 530100, Guangxi, Peoples R China
来源：
JOURNAL OF NANOELECTRONICS AND OPTOELECTRONICS | 2024年 / 19卷 / 07期
关键词：
Microstrip Antenna; Miniaturization and Broadband; Multi-Objective Optimization Design; Adaptive BF Neural Network;
D O I：
10.1166/jno.2024.3626
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：
Antenna plays an important role in modern communication. Accurate calculation of antenna structure to obtain reasonable electromagnetic characteristic parameters is an important part of antenna design. With the increasing complexity of the antenna structure, a large number of numerical calculations are required in the design process to determine the optimal structure size. Therefore, it's necessary to study the fast optimization algorithm of antenna multi-objective (antenna bandwidth, gain, polarization characteristics, etc) optimization design method. In this paper, a new adaptive BF neural network is proposed to optimize the resonant frequency and size structure of dual frequency circular polarization microstrip antenna, so as to improve the efficiency of antenna design.
引用
收藏
页码：768 / 772
页数：5
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