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FET model parameter extraction based on optimization with multiplane data-fitting and bidirectional search-a new concept

机译:基于多平面数据拟合和双向搜索优化的FET模型参数提取新概念

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摘要

A new optimization formulation is presented for efficient FET model parameter extraction, in which data-fitting is carried out in multi reference planes instead of only one, and the objective function is minimized by a bidirectional search technique. As an example of application, all parameters of a commonly used 15-element small-signal FET equivalent circuit model are clearly identified from only one set of measured S-parameters. A self-consistent generation of starting values can be involved regarding the FET in the passive pinch-off operating mode. Moreover, applying multi-bias data-fitting, which is performed without increasing the number of ordinary optimization variables, yields a robust determination of both the overall bias-independent parasitics and the bias-dependent intrinsic elements. For demonstration results are presented for a 0.5-/spl mu/m MESFET.
机译:提出了一种新的优化公式,用于有效的FET模型参数提取,其中在多个参考平面而不是仅在一个参考平面中进行数据拟合,并且通过双向搜索技术将目标函数最小化。作为应用示例,仅从一组测量的S参数中即可清楚地识别出常用的15元素小信号FET等效电路模型的所有参数。关于在被动夹断工作模式下的FET,可能涉及起始值的自洽生成。此外,应用多偏置数据拟合(无需增加普通优化变量的数量即可执行)可对整个独立于偏置的寄生因素和独立于偏置的本征元素进行可靠的确定。为了演示,给出了0.5- / spl mu / m MESFET的结果。

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