An accurate neural network model of FET for intermodulation and power analysis

J. Rousset, Y. Harkouss, J. Collantes, M. Campovecchio
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引用次数: 22

Abstract

An accurate nonlinear FET model based on a Neural Network representation of the drain current source has been developed to predict intermodulation distortion as well as output power performance. This new neural network model has been implemented in a commercial harmonic balance simulator and its efficiency is evidenced by a comparison with an empirical model (Tajima). The accuracy of the proposed model is verified by active load-pull measurements on a Texas HFET at 10 GHz.
用于互调制和功率分析的FET精确神经网络模型
基于漏极电流源的神经网络表示,建立了一个精确的非线性场效应管模型,用于预测互调失真和输出功率性能。该神经网络模型已在商业谐波平衡模拟器中实现,并与经验模型(Tajima)进行了比较,证明了其有效性。通过对德克萨斯HFET在10ghz频率下的主动负载-拉力测量,验证了所提模型的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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