@inproceedings{99c9ef56eb014686b33b089d58e9cc08,
title = "Photo-electro characterization and modeling of organic light-emitting diodes by using a radial basis neural network",
abstract = "In this paper we present a new RBFNNs neural networks based model to relate the overall OLEDs electroluminescent density as a function of the voltage and current at different wavelengths. The polymer-based OLEDs considered in this paper are realized in the Optoelectronic Organic Semiconductor Devices Laboratory at Ben Gurion University of the Negev. The simulation results show a good agreement between the experimental data and those obtained with the proposed model. This results prove that the model is capable of repeating and interpreting the experimental data.",
keywords = "Electroluminescent spectrum, OLED, RBFNNs neural networks",
author = "Barnea, \{Shiran Nabha\} and \{Lo Sciuto\}, Grazia and Nathaniel Hai and Rafi Shikler and Giacomo Capizzi and Marcin Wozniak and Dawid Polap",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 16th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2017 ; Conference date: 11-06-2017 Through 15-06-2017",
year = "2017",
doi = "10.1007/978-3-319-59060-8\_34",
language = "English",
isbn = "9783319590592",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "378--389",
editor = "Zurada, \{Jacek M.\} and Zadeh, \{Lotfi A.\} and Ryszard Tadeusiewicz and Leszek Rutkowski and Marcin Korytkowski and Rafal Scherer",
booktitle = "Artificial Intelligence and Soft Computing - 16th International Conference, ICAISC 2017, Proceedings",
address = "Germany",
}