利用神经网络对辐射电磁干扰下的PCB结构进行分类

Proceedings. Asia-Pacific Conference on Environmental Electromagnetics. CEEM'2000 (IEEE Cat. No.00EX402) Pub Date : 2000-05-03 DOI:10.1109/CEEM.2000.853911

K. Aunchaleevarapan, K. Paithoonwatanakij, Y. Preampraneerach, W. Khan-ngern, S. Nitta

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引用次数: 9

摘要

本文提出了一种利用神经网络对具有多种结构的印刷电路板进行频谱识别的分类方法。学习过程是通过给神经网络22种PCB结构的不同辐射发射光谱来完成的。训练后的神经网络能够成功地预测PCB的结构。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Classification of PCB configurations from radiated EMI by using neural network

This paper presents a method of classifications of printed circuit board (PCB) with having several configuration by using neural network to recognized its spectrum. The learning process is accomplished by giving the neural network the different radiated emission spectra of 22 PCB configurations. The trained neural network is successfully able to predict the PCB configurations.

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来源期刊

Proceedings. Asia-Pacific Conference on Environmental Electromagnetics. CEEM'2000 (IEEE Cat. No.00EX402)

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