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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...

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Detalles Bibliográficos
Autores principales: Cheng, Lin, Lu, Hongliang, Yan, Silu, Liu, Chen, Qiao, Jiantao, Qi, Junjun, Cheng, Wei, Zhang, Yimen, Zhang, Yuming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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.
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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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