A THz Waveguide Bandpass Filter Design Using an Artificial Neural Network

This paper presents a 300 GHz waveguide bandpass filter based on asymmetric inductive irises. The coupling matrix synthesis technique is used to design a 6-pole Chebyshev filter. In addition, an artificial neural network is applied to provide the filter geometries using the desired frequency respons...

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Detalles Bibliográficos
Autores principales: Lin, Chu-Hsuan, Cheng, Yu-Hsiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9231129/
https://www.ncbi.nlm.nih.gov/pubmed/35744455
http://dx.doi.org/10.3390/mi13060841
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author Lin, Chu-Hsuan
Cheng, Yu-Hsiang
author_facet Lin, Chu-Hsuan
Cheng, Yu-Hsiang
author_sort Lin, Chu-Hsuan
collection PubMed
description This paper presents a 300 GHz waveguide bandpass filter based on asymmetric inductive irises. The coupling matrix synthesis technique is used to design a 6-pole Chebyshev filter. In addition, an artificial neural network is applied to provide the filter geometries using the desired frequency response. The optimized filter is fabricated by the computer numeric controlled milling process. The measurement results show that the insertion loss is less than 3 dB and the return loss is better than 17 dB in the range 276–310 GHz.
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spelling pubmed-92311292022-06-25 A THz Waveguide Bandpass Filter Design Using an Artificial Neural Network Lin, Chu-Hsuan Cheng, Yu-Hsiang Micromachines (Basel) Article This paper presents a 300 GHz waveguide bandpass filter based on asymmetric inductive irises. The coupling matrix synthesis technique is used to design a 6-pole Chebyshev filter. In addition, an artificial neural network is applied to provide the filter geometries using the desired frequency response. The optimized filter is fabricated by the computer numeric controlled milling process. The measurement results show that the insertion loss is less than 3 dB and the return loss is better than 17 dB in the range 276–310 GHz. MDPI 2022-05-27 /pmc/articles/PMC9231129/ /pubmed/35744455 http://dx.doi.org/10.3390/mi13060841 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lin, Chu-Hsuan
Cheng, Yu-Hsiang
A THz Waveguide Bandpass Filter Design Using an Artificial Neural Network
title A THz Waveguide Bandpass Filter Design Using an Artificial Neural Network
title_full A THz Waveguide Bandpass Filter Design Using an Artificial Neural Network
title_fullStr A THz Waveguide Bandpass Filter Design Using an Artificial Neural Network
title_full_unstemmed A THz Waveguide Bandpass Filter Design Using an Artificial Neural Network
title_short A THz Waveguide Bandpass Filter Design Using an Artificial Neural Network
title_sort thz waveguide bandpass filter design using an artificial neural network
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9231129/
https://www.ncbi.nlm.nih.gov/pubmed/35744455
http://dx.doi.org/10.3390/mi13060841
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