Title :
Artificial neural network modeling for Extrinsic capacitance of FinFET
Author :
Wei-Chuan Chen ; Chang-Pao Chang ; Ming-Kai Kang ; Ting-Ui Huang ; Kai-Bin Wu ; Ruey-Beei Wu
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Abstract :
Artificial neural networks (ANNs) have been applied as an efficient machine-learning tool to model many complex electromagnetic problems recently. This paper gives a comprehensive description on fast extraction of the extrinsic capacitance for 3D FinFET transistors using Q3D with different sizes. This extraction method is later coupled with artificial neural networks to form a controllable model with good balance between accuracy and efficiency. The error analysis of this model is also given at the end of the context..
Keywords :
MOSFET; capacitance; electronic engineering computing; neural nets; semiconductor device models; FinFET; Q3D; artificial neural network; extrinsic capacitance; machine learning tool; Artificial neural networks; Capacitance; Decision support systems; FinFETs; Microwave transistors; Training; Artificial Neural Networks; Extrinsic Capacitance; FinFET;
Conference_Titel :
Electrical Performance of Electronic Packaging and Systems (EPEPS), 2014 IEEE 23rd Conference on
Print_ISBN :
978-1-4799-3641-0
DOI :
10.1109/EPEPS.2014.7103604