Shape Modeling of Microstrip Filters Based on Convolutional Neural Network

被引：9

作者：

Luo, Hai-Ying ^{[1
]}

Shao, Wei ^{[1
]}

Ding, Xiao ^{[1
]}

Wang, Bing-Zhong ^{[1
]}

Cheng, Xi ^{[2
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Phys, Chengdu 611731, Peoples R China

[2] Xinjiang Agr Univ, Sch Comp & Informat Engn, Urumqi 830052, Xinjiang, Peoples R China

来源：

IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS | 2022年 / 32卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Shape; Training; Convolutional neural networks; Strips; Interpolation; Splines (mathematics); Microwave imaging; Convolutional neural network (CNN); cubic spline interpolation; microstrip filters; shape modeling; DESIGN;

D O I：

10.1109/LMWC.2022.3162414

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：

An effective convolutional neural network (CNN) with the transfer function (TF) is proposed for shape modeling of electromagnetic (EM) behaviors of microstrip filters. The input of CNN is the images of metallic strips instead of the geometric parameters. To define the training samples, a one-to-one relation between the strip contour and the knot positions is built with a shape-changing technique based on cubic spline interpolation. The proposed model is confirmed with an example of a microstrip/coplanar waveguide (CPW) ultrawideband (UWB) filter. Compared with the parametric artificial neural network (ANN) and the shape ANN, the proposed model shows the improvement of design flexibility and the expansion of the solution domain.

引用

页码：1019 / 1022

页数：4

共 50 条

[21] Trained convolutional neural network based on selected beta filters for Arabic letter recognition
ElAdel, Asma
Zaied, Mourad
Ben Amar, Chokri
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2019, 9 (03)
[22] Soft Sensor Modeling of Mill Level Based on Convolutional Neural Network
Wei, Jie
Guo, Lei
Xu, Xinying
Yan, Gaowei
2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 4738 - 4743
[23] Thermal Error Modeling of Rotary Axis Based on Convolutional Neural Network
Wu Chengyang
Xiang Sitong
Xiang Wansheng
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 2021, 143 (05):
[24] An Opinion Spam Detection Method Based on Multi-Filters Convolutional Neural Network
Wang, Ye
Liu, Bixin
Wu, Hongjia
Zhao, Shan
Cai, Zhiping
Li, Donghui
Fong, Cheang Chak
CMC-COMPUTERS MATERIALS & CONTINUA, 2020, 65 (01): : 355 - 367
[25] Automatic Semivariogram Modeling by Convolutional Neural Network
Jo, Honggeun
Pyrcz, Michael J.
MATHEMATICAL GEOSCIENCES, 2022, 54 (01) : 177 - 205
[26] Automatic Semivariogram Modeling by Convolutional Neural Network
Honggeun Jo
Michael J. Pyrcz
Mathematical Geosciences, 2022, 54 : 177 - 205
[27] Convolutional Neural Network for Coupling Matrix Extraction of Microwave Filters
Sallam, Tarek
Attiya, Ahmed M.
APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY JOURNAL, 2022, 37 (07): : 805 - 810
[28] Investigating Existing Techniques for Designing Convolutional Neural Network Filters
Karuppasamy, ArunaDevi
Abdessalem, Abdelhamid
Hedjam, Rachid
Zidoum, Hamza M.
2019 10TH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND NETWORKING TECHNOLOGIES (ICCCNT), 2019,
[29] Artificial Neural Network Modeling Of Microwave Filters
Raghavan, S.
Ilango, C.
INCEMIC 2006: 9TH INTERNATIONAL CONFERENCE ON ELECTROMAGNETIC INTERFERENCE AND COMPATIBILITY, PROCEEDINGS, 2006, : 561 - 564
[30] ELECTRODYNAMIC MODELING OF MICROSTRIP FILTERS BASED ON COUPLED LINES
NIKOLSKAYA, TI
NIKOLSKIY, VV
TSEDILIN, VI
KOMLEVA, VK
TELECOMMUNICATIONS AND RADIO ENGINEERING, 1990, 45 (09) : 115 - 119

← 1 2 3 4 5 →