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S-functions behavioral model order reduction based on narrowband modulated large-signal network analyzer measurements

机译:基于窄带调制大信号网络分析仪测量的S函数行为模型降阶

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In this paper we report for the first time on order reduction applied to S-functions behavioral models. The most dominant model parameters are selected based on the relative uncertainty of their estimated values evaluated against a threshold value. The selection procedure is performed on the same measurement data that is used to extract the model and obtained using a large-signal network analyzer. High level of model order reduction, achieved without any substantial loss of the prediction accuracy, is demonstrated on S-functions extracted for a packaged pHEMT device.
机译:在本文中,我们首次报告了应用于S函数行为模型的降阶。基于相对于阈值评估的估计值的相对不确定性来选择最主要的模型参数。选择过程对用于提取模型并使用大信号网络分析仪获得的相同测量数据执行。在为封装的pHEMT设备提取的S函数上,证明了在不大幅降低预测精度的情况下实现的高水平模型降阶。

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