In this paper, a novel artificial neural network (ANN)‐based nonlinear output current model with accurate high‐order derivatives is presented. The proposed model can guarantee high precision of the drain current and its high‐order derivatives simultaneously. The existing traditional equation‐based models are analyzed to demonstrate their limits and inaccurate modeling performance of high‐order derivatives. Aiming at maintaining high accuracy of the drain current and its derivatives at the same time, the ANN has been used iteratively. This method, which inherits the advantage of ANN model, obtains higher accuracy than existing ANN model as well as traditional equation‐based models. The effectiveness of the model has been verified by comparing the modeled and measured results for a GaAs pHEMT.

中文翻译：

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具有精确高阶导数的基于新型人工神经网络的GaAs pHEMT非线性输出电流模型

本文提出了一种基于新型人工神经网络（ANN）的非线性输出电流模型，该模型具有精确的高阶导数。提出的模型可以同时保证漏极电流及其高阶导数的高精度。分析了现有的基于等式的传统模型，以证明其局限性和高阶导数的不正确建模性能。为了同时保持漏极电流及其导数的高精度，ANN被迭代使用。这种方法继承了ANN模型的优势，比现有的ANN模型以及传统的基于方程的模型具有更高的准确性。通过比较GaAs pHEMT的建模结果和测量结果，验证了模型的有效性。