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.

Photo-electro characterization and modeling of organic light-emitting diodes by using a radial basis neural network

LO SCIUTO, GRAZIA;CAPIZZI, GIACOMO;
2017-01-01

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.
2017
9783319590592
Electroluminescent spectrum; OLED; RBFNNs neural networks; Theoretical Computer Science; Computer Science (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/298291
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