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Application and Prospect of Artificial Intelligence Methods in Signal Integrity Prediction and Optimization of Microsystems

Microsystems are widely used in 5G, the Internet of Things, smart electronic devices and other fields, and signal integrity (SI) determines their performance. Establishing accurate and fast predictive models and intelligent optimization models for SI in microsystems is extremely essential. Recently,...

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Detalles Bibliográficos
Autores principales: Shan, Guangbao, Li, Guoliang, Wang, Yuxuan, Xing, Chaoyang, Zheng, Yanwen, Yang, Yintang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9958958/
https://www.ncbi.nlm.nih.gov/pubmed/36838043
http://dx.doi.org/10.3390/mi14020344
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author Shan, Guangbao
Li, Guoliang
Wang, Yuxuan
Xing, Chaoyang
Zheng, Yanwen
Yang, Yintang
author_facet Shan, Guangbao
Li, Guoliang
Wang, Yuxuan
Xing, Chaoyang
Zheng, Yanwen
Yang, Yintang
author_sort Shan, Guangbao
collection PubMed
description Microsystems are widely used in 5G, the Internet of Things, smart electronic devices and other fields, and signal integrity (SI) determines their performance. Establishing accurate and fast predictive models and intelligent optimization models for SI in microsystems is extremely essential. Recently, neural networks (NNs) and heuristic optimization algorithms have been widely used to predict the SI performance of microsystems. This paper systematically summarizes the neural network methods applied in the prediction of microsystem SI performance, including artificial neural network (ANN), deep neural network (DNN), recurrent neural network (RNN), convolutional neural network (CNN), etc., as well as intelligent algorithms applied in the optimization of microsystem SI, including genetic algorithm (GA), differential evolution (DE), deep partition tree Bayesian optimization (DPTBO), two stage Bayesian optimization (TSBO), etc., and compares and discusses the characteristics and application fields of the current applied methods. The future development prospects are also predicted. Finally, the article is summarized.
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spelling pubmed-99589582023-02-26 Application and Prospect of Artificial Intelligence Methods in Signal Integrity Prediction and Optimization of Microsystems Shan, Guangbao Li, Guoliang Wang, Yuxuan Xing, Chaoyang Zheng, Yanwen Yang, Yintang Micromachines (Basel) Review Microsystems are widely used in 5G, the Internet of Things, smart electronic devices and other fields, and signal integrity (SI) determines their performance. Establishing accurate and fast predictive models and intelligent optimization models for SI in microsystems is extremely essential. Recently, neural networks (NNs) and heuristic optimization algorithms have been widely used to predict the SI performance of microsystems. This paper systematically summarizes the neural network methods applied in the prediction of microsystem SI performance, including artificial neural network (ANN), deep neural network (DNN), recurrent neural network (RNN), convolutional neural network (CNN), etc., as well as intelligent algorithms applied in the optimization of microsystem SI, including genetic algorithm (GA), differential evolution (DE), deep partition tree Bayesian optimization (DPTBO), two stage Bayesian optimization (TSBO), etc., and compares and discusses the characteristics and application fields of the current applied methods. The future development prospects are also predicted. Finally, the article is summarized. MDPI 2023-01-29 /pmc/articles/PMC9958958/ /pubmed/36838043 http://dx.doi.org/10.3390/mi14020344 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 Review
Shan, Guangbao
Li, Guoliang
Wang, Yuxuan
Xing, Chaoyang
Zheng, Yanwen
Yang, Yintang
Application and Prospect of Artificial Intelligence Methods in Signal Integrity Prediction and Optimization of Microsystems
title Application and Prospect of Artificial Intelligence Methods in Signal Integrity Prediction and Optimization of Microsystems
title_full Application and Prospect of Artificial Intelligence Methods in Signal Integrity Prediction and Optimization of Microsystems
title_fullStr Application and Prospect of Artificial Intelligence Methods in Signal Integrity Prediction and Optimization of Microsystems
title_full_unstemmed Application and Prospect of Artificial Intelligence Methods in Signal Integrity Prediction and Optimization of Microsystems
title_short Application and Prospect of Artificial Intelligence Methods in Signal Integrity Prediction and Optimization of Microsystems
title_sort application and prospect of artificial intelligence methods in signal integrity prediction and optimization of microsystems
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9958958/
https://www.ncbi.nlm.nih.gov/pubmed/36838043
http://dx.doi.org/10.3390/mi14020344
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