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By using grey system and Neural-Fuzzy Network methods to obtain the threshold voltage of submicron n-MOSFET DUTs

机译:通过使用灰色系统和神经网络方法获得亚微米n-MOSFET DUT的阈值电压

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In this paper, two techniques are used to obtain the complex non-linear threshold voltage (Vth) data in sub-micrometer MOSFET DUTs via the grey system (GS) method and Neural-Fuzzy Network (NFN). This paper presents the implement procedure of these two models in Vth predictions. Moreover, comparisons among the GS and NFN output results are carried out. Here, it will be used to analyze the Vth inclination of submicron MOSFET DUTs due to the device geometric effect. Introducing comparison between the measured and prediction characteristics of Vth show good matching for a wide domain of channel width (W), length (L), and bias conditions. Then, the implemented procedure may be proper for BSIM model parameters extraction.
机译:本文使用两种技术通过灰色系统(GS)方法和神经模糊网络(NFN)获得亚微米MOSFET DUT中的复杂非线性阈值电压(Vth)数据。本文介绍了这两种模型在Vth预测中的实现过程。此外,还对GS和NFN的输出结果进行了比较。在这里,由于器件的几何效应,它将用于分析亚微米MOSFET DUT的Vth倾斜度。在Vth的测量特性和预测特性之间进行的比较显示出在宽的通道宽度(W),长度(L)和偏置条件下都具有良好的匹配性。然后,所实施的过程对于BSIM模型参数提取可能是适当的。

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