Parameters Extraction for Equivalent Circuit Model Based on Artificial Intelligence

Autor:	Peng Zhao, Linchun Liu, Zhimin Guan, Gan Shen, Gaofeng Wang
Rok vydání:	2019
Předmět:	Training set Electromagnetics Computer science business.industry Computer Science::Neural and Evolutionary Computation Extraction (chemistry) Equivalent circuit Extraction methods Artificial intelligence Inductor business Electromagnetic simulation Data modeling
Zdroj:	2019 IEEE International Conference on Computational Electromagnetics (ICCEM).
DOI:	10.1109/compem.2019.8779062
Popis:	In this paper, a novel parameter extraction method for equivalent circuit based on artificial intelligence (AI) technique is proposed. The Y-parameters calculated by UltraEM®, which is a high efficient electromagnetic simulation tool, are used as training data to establish corresponding AI model. With this AI model, the parameters of the equivalent circuit can be efficiently obtained by optimization method. An example of a spiral inductor is given to demonstrate the extraction procedure and validate the results.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5886b35342e4fe9b730dcb151ede7dfb https://doi.org/10.1109/compem.2019.8779062 Zobrazit plný text záznamu