真空电子技术Issue(1)：16-21,6.DOI:10.16540/j.cnki.cn11-2485/tn.2024.01.04
基于神经网络的超材料窗片反向设计研究
An Optimal Design of Metamaterial Window Based on Neural Networks
谷炳毅 1曹耀耀 1王汀略 1李俊延 1曾旭 2潘攀 2柏宁丰1
作者信息
- 1. 东南大学电子科学与工程学院 ,江苏南京 210096
- 2. 北京真空电子技术研究所 ,北京 100015
- 折叠
摘要
Abstract
Compared with solid-state devices,vacuum electronic devices can provide higher power and wider bandwidth.As an important component,the microwave window is used to isolate the internal and external environment of the vacuum electronic device,maintain the high vacuum inside the device,and transmit high-energy electromagnetic wave.At present,the performance of traditional microwave window constrains the performance of broadband high-frequency vacuum devices.Therefore,a design method of metamaterial structure using neural network algorithm is proposed which can realize a broadband micro-wave metamaterial window with low reflection and low voltage standing wave ratio.The nonlinear fitting effect of neural network is used to establish a mapping relationship between the window structure and its spectrum,thus avoiding the complicated solving process of Maxwell's equations,improving the simulation speed of spectrum performance and simplifying the design process.By designing and training the bidirec-tional neural network,the reverse design of window is achieved,by which the structural parameters can be generated only by inputting the corresponding target spectral characteristic parameters.关键词
真空电子器件/输能窗/超材料/人工神经网络Key words
Vacuum electronic device/Microwave window/Metamaterial/Artificial neural network分类
电子信息工程引用本文复制引用
谷炳毅,曹耀耀,王汀略,李俊延,曾旭,潘攀,柏宁丰..基于神经网络的超材料窗片反向设计研究[J].真空电子技术,2024,(1):16-21,6.
