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Vol. 214, Issue 7, July 2017, pp. 53-57




Modeling Nanoscale FinFET Performance by a Neural Network Method

1Jin He*, 1Guoqing Hu, 1Bing Xie, 1Guangjin Ma, 2Ping He, 3Lei Song, 1Chunlai Li, 1Daye Lin, 1Jingjing Liu, 1Ying Yu, 1Zhangyuan Chen and 1Zhiping Zhou

1 Peking University Shenzhen SoC Key Laboratory, Shenzhen 518057, China
2 Shenzhen Emperor Electronic Technology Co., Ltd, Nanshan District, Shenzhen518108, China
3 Shenzhen SuperD Co. Ltd, Huaqiaocheng, Nanshan District, Shenzhen 518053, China
Tel.: 15013563293

* E-mail: frankhe@pku.edu.cn


Received: 1 June 2017 /Accepted: 12 July 2017 /Published: 31 July 2017

Digital Sensors and Sensor Sysstems


Abstract: This paper presents a neural network method to model nanometer FinFET performance. The principle of this method is firstly introduced and its application in modeling DC and conductance characteristics of nanoscale FinFET transistor is demonstrated in detail. It is shown that this method does not need parameter extraction routine while its prediction of the transistor performance has a small relative error within 1 % compared with measured data, thus this new method is as accurate as the physics based surface potential model.


Keywords: nanometer FinFET, compact modeling and simulation, network method, accuracy


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