Impact of Sampling Domain and Number of Samples on the Accuracy of Large-Signal Multisine Measurement-Based Behavioral Model

Maciej Myslinski; Dominique Schreurs; Bart Nauwelaers

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Impact of Sampling Domain and Number of Samples on the Accuracy of Large-Signal Multisine Measurement-Based Behavioral Model

机译：采样域和样本数量对基于大信号多正弦测量的行为模型精度的影响

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摘要

This article evaluates two alternative ways to execute the sampling of modulated data for large-signal behavioral modeling. We show that the nonlinear metric domain uniform sampling outperforms the time-domain uniform approach, and examine how the level of improvement depends on the number of samples used for model generation.

机译：本文评估了两种替代方法来执行大信号行为建模的调制数据采样。我们证明了非线性度量域统一采样的性能优于时域统一方法，并研究了改进程度如何取决于用于模型生成的样本数量。

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来源
《International journal of RF and microwave computer-aided engineering》 |2010年第4期|P.374-381|共8页
作者
Maciej Myslinski; Dominique Schreurs; Bart Nauwelaers;
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作者单位

K.U.Leuven, Div. ESAT-TELEMIC, Leuven B-3001, Belgium;

K.U.Leuven, Div. ESAT-TELEMIC, Leuven B-3001, Belgium;

K.U.Leuven, Div. ESAT-TELEMIC, Leuven B-3001, Belgium;

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原文格式 PDF
正文语种 eng
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关键词
behavioral modeling; large-signal measurements; sampling; multisine data reduction;

机译：行为建模;大信号测量;采样;多正弦数据约简;
入库时间 2022-08-17 13:30:14

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Impact of Sampling Domain and Number of Samples on the Accuracy of Large-Signal Multisine Measurement-Based Behavioral Model

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