Title :
Easy modeling of OTFTs using neural networks
Author :
Lagziri, M. ; Picos, R. ; Bentaibi, N. ; Boussouis, M. ; Garcia-Moreno, E.
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;
Conference_Titel :
Electron Devices (CDE), 2011 Spanish Conference on
Conference_Location :
Palma de Mallorca
Print_ISBN :
978-1-4244-7863-7
DOI :
10.1109/SCED.2011.5744186
