基于S参数的高Q MCM电感的指数梯度学习实验建模

Jinsong Zhao, W. Dai, R. Frye, K. Tai
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引用次数: 35

摘要

集总电感器是集成在MCM基板上的无线/射频电路中非常理想的无源元件。本文利用S参数公式和指数梯度法对晶片上高频测量的电感进行建模。S参数公式使我们能够理解模型内的相移效应,而指数梯度学习算法为我们提供了比梯度下降算法更鲁棒和更好的拟合技术。所有S参数的幅值和相位都适合于我们所构造的所有电感。结果表明,即使在MCM-D技术中,分布效应的相移也不容忽视。所得到的实验模型为电路设计和数值表征提供了测量验证的坚实基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
S parameter-based experimental modeling of high Q MCM inductor with exponential gradient learning algorithm
Lumped inductors are very desirable passive components in wireless/RF circuits integrated on MCM substrate. This paper models the inductor from on-wafer high frequency measurement by utilizing the S parameter formulation and exponential gradient method. The S parameter formulation enables us to understand the phase shifting effects within the model while the exponential gradient learning algorithm provides us with a more robust and better fitting technique than the gradient descent algorithm. Both the magnitudes and phases of all S parameters fit well for all the inductors we constructed. It is shown that the phase shifting of the distributed effects should not be neglected even in MCM-D technology. The resulting experimental model provides measurement-verified solid ground for circuit design and numerical characterization.
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