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An Aging Small-Signal Model for Degradation Prediction of Microwave Heterojunction Bipolar Transistor S-Parameters Based on Prior Knowledge Neural Network
In this paper, an aging small-signal model for degradation prediction of microwave heterojunction bipolar transistor (HBT) S-parameters based on prior knowledge neural networks (PKNNs) is explored. A dual-extreme learning machine (D-ELM) structure with an adaptive genetic algorithm (AGA) optimizatio...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673388/ https://www.ncbi.nlm.nih.gov/pubmed/38004880 http://dx.doi.org/10.3390/mi14112023 |
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author | Cheng, Lin Lu, Hongliang Yan, Silu Liu, Chen Qiao, Jiantao Qi, Junjun Cheng, Wei Zhang, Yimen Zhang, Yuming |
author_facet | Cheng, Lin Lu, Hongliang Yan, Silu Liu, Chen Qiao, Jiantao Qi, Junjun Cheng, Wei Zhang, Yimen Zhang, Yuming |
author_sort | Cheng, Lin |
collection | PubMed |
description | In this paper, an aging small-signal model for degradation prediction of microwave heterojunction bipolar transistor (HBT) S-parameters based on prior knowledge neural networks (PKNNs) is explored. A dual-extreme learning machine (D-ELM) structure with an adaptive genetic algorithm (AGA) optimization process is used to simulate the fresh S-parameters of InP HBT devices and the degradation of S-parameters after accelerated aging, respectively. In addition to the reliability parametric inputs of the original aging problem, the S-parameter degradation trend obtained from the aging small-signal equivalent circuit is used as additional information to inject into the D-ELM structure. Good agreement was achieved between measured and predicted results of the degradation of S-parameters within a frequency range of 0.1 to 40 GHz. |
format | Online Article Text |
id | pubmed-10673388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106733882023-10-30 An Aging Small-Signal Model for Degradation Prediction of Microwave Heterojunction Bipolar Transistor S-Parameters Based on Prior Knowledge Neural Network Cheng, Lin Lu, Hongliang Yan, Silu Liu, Chen Qiao, Jiantao Qi, Junjun Cheng, Wei Zhang, Yimen Zhang, Yuming Micromachines (Basel) Article In this paper, an aging small-signal model for degradation prediction of microwave heterojunction bipolar transistor (HBT) S-parameters based on prior knowledge neural networks (PKNNs) is explored. A dual-extreme learning machine (D-ELM) structure with an adaptive genetic algorithm (AGA) optimization process is used to simulate the fresh S-parameters of InP HBT devices and the degradation of S-parameters after accelerated aging, respectively. In addition to the reliability parametric inputs of the original aging problem, the S-parameter degradation trend obtained from the aging small-signal equivalent circuit is used as additional information to inject into the D-ELM structure. Good agreement was achieved between measured and predicted results of the degradation of S-parameters within a frequency range of 0.1 to 40 GHz. MDPI 2023-10-30 /pmc/articles/PMC10673388/ /pubmed/38004880 http://dx.doi.org/10.3390/mi14112023 Text en © 2023 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 Cheng, Lin Lu, Hongliang Yan, Silu Liu, Chen Qiao, Jiantao Qi, Junjun Cheng, Wei Zhang, Yimen Zhang, Yuming An Aging Small-Signal Model for Degradation Prediction of Microwave Heterojunction Bipolar Transistor S-Parameters Based on Prior Knowledge Neural Network |
title | An Aging Small-Signal Model for Degradation Prediction of Microwave Heterojunction Bipolar Transistor S-Parameters Based on Prior Knowledge Neural Network |
title_full | An Aging Small-Signal Model for Degradation Prediction of Microwave Heterojunction Bipolar Transistor S-Parameters Based on Prior Knowledge Neural Network |
title_fullStr | An Aging Small-Signal Model for Degradation Prediction of Microwave Heterojunction Bipolar Transistor S-Parameters Based on Prior Knowledge Neural Network |
title_full_unstemmed | An Aging Small-Signal Model for Degradation Prediction of Microwave Heterojunction Bipolar Transistor S-Parameters Based on Prior Knowledge Neural Network |
title_short | An Aging Small-Signal Model for Degradation Prediction of Microwave Heterojunction Bipolar Transistor S-Parameters Based on Prior Knowledge Neural Network |
title_sort | aging small-signal model for degradation prediction of microwave heterojunction bipolar transistor s-parameters based on prior knowledge neural network |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673388/ https://www.ncbi.nlm.nih.gov/pubmed/38004880 http://dx.doi.org/10.3390/mi14112023 |
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