一种基于k均值聚类算法的眼图参数测量方法

Bo Gao, Keyu Wei, L. Tong
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引用次数: 2

摘要

眼图及其参数测量是高速数字信号表示和分析的重要手段。本文将数据挖掘中常用的K-means算法引入到眼图参数测量中。本文所提出的方法具有K-means算法的优点,能够自动、有效地工作。用矢量网络分析仪(VNA)测量差分线,并根据测量的S参数生成不同数据速率下的眼图。该方法用于测量这些眼图。实验结果表明,该方法效果良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An eye diagram parameters measurement method based on K-means clustering algorithm
Eye diagram and its parameters measurement are very important to represent and analyze the high-speed digital signal. In this paper, K-means algorithm, which is popular in data mine, is introduced into the eye diagram parameters measurement. With the advantage of K-means algorithm, the method proposed in this paper can work automatically and effectively. A differential line is measured by vector network analyzer (VNA) and several eye diagrams at different data rates are generated by the measured S parameters. The method is used to measure these eye diagrams. Experiment results show that this method works very well.
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