DocumentCode
2710832
Title
Neural network technique for the speed-up of Monte-Carlo based semiconductor simulators
Author
Matei, R. ; Dima, G. ; Profirescu, M.D.
Author_Institution
R&D Centre, Univ. Politehnica of Bucharest, Romania
Volume
1
fYear
2000
fDate
2000
Firstpage
359
Abstract
The paper presents a way for improving the simulation time of the Monte-Carlo based simulators using a neural network structure. A multi-layered feed-forward neural network trained with a quasi-Newton algorithm was used. As an example, the extraction of the bulk transport parameters of a III-V compound semiconductor is discussed
Keywords
III-V semiconductors; Monte Carlo methods; Newton method; feedforward neural nets; III-V compound semiconductor; Monte Carlo simulation; bulk transport; multilayered feedforward neural network; quasi-Newton algorithm; Computational modeling; Computer networks; Electronic mail; Feedforward neural networks; Feedforward systems; III-V semiconductor materials; Multi-layer neural network; Neural networks; Parallel processing; Research and development;
fLanguage
English
Publisher
ieee
Conference_Titel
Semiconductor Conference, 2000. CAS 2000 Proceedings. International
Conference_Location
Sinaia
Print_ISBN
0-7803-5885-6
Type
conf
DOI
10.1109/SMICND.2000.890254
Filename
890254
Link To Document