DocumentCode
2857560
Title
Easy modeling of OTFTs using neural networks
Author
Lagziri, M. ; Picos, R. ; Bentaibi, N. ; Boussouis, M. ; Garcia-Moreno, E.
fYear
2011
fDate
8-11 Feb. 2011
Firstpage
1
Lastpage
4
Abstract
In this paper we present a model of organic TFT based on neural network. This approach allows a fast and easy way to model devices having a strong non-linear behavior, without entering in the device physics. The same network structure can be adapted for different devices after a training stage were the connection weights between the network elements are defined. Results show that few DC measures are required to fit the model to the whole I-V output characteristics.
Keywords
electronic engineering computing; neural nets; organic semiconductors; semiconductor device models; thin film transistors; DC measures; I-V output characteristics; OTFT; connection weights; device physics; network elements; network structure; neural networks; organic TFT; strong nonlinear behavior; Adaptation model; Artificial neural networks; Integrated circuit modeling; Neurons; Organic thin film transistors; Training; Organic TFT; modeling; neural networks; optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Electron Devices (CDE), 2011 Spanish Conference on
Conference_Location
Palma de Mallorca
Print_ISBN
978-1-4244-7863-7
Type
conf
DOI
10.1109/SCED.2011.5744186
Filename
5744186
Link To Document