Deep Neural Network for Device Modeling

Yuan Lei, Xiao Huo, Beiping Yan
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引用次数: 14

Abstract

High quality and high accuracy device model is an essential link from device simulation to circuit simulation. However, device model using artificial neural network (ANN) often causes unphysical behaviors. A novel deep neural network (DNN) approach for device modeling is proposed in this article. A novel regression method is used to eliminate unphysical behaviors. The developed DNN model has been verified by a complete set of physical measured data with smooth and accurate predicted results.
用于设备建模的深度神经网络
高质量、高精度的器件模型是器件仿真到电路仿真的重要环节。然而,基于人工神经网络(ANN)的设备模型往往会产生非物理行为。本文提出了一种新的用于器件建模的深度神经网络方法。一种新的回归方法用于消除非物理行为。所建立的深度神经网络模型已被一套完整的物理实测数据所验证,预测结果平稳、准确。
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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