Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/106131
Título: VLC Color Shift Keying Detection Using Neural Networks
Autores/as: Delgado Rajó, Francisco Alberto 
Travieso González, Carlos Manuel 
González Hernández,Oswaldo Bernabé 
Pérez Jiménez, Rafael 
Clasificación UNESCO: 3307 Tecnología electrónica
Fecha de publicación: 2018
Conferencia: 10th IEEE Latin-American Conference on Communications (IEEE LATINCOM) 
Resumen: In this work, a new Visible Light Communication system employing Color Shift Keying is presented, evaluated by means of a prototype. The variations of the ambient lighting constitute an interference at the detection of the symbols of the color constellation used in the transmitter. These variations are generally low speed compared to those due to data transmission. This paper provides two superimposed solutions for this problem: On the one hand, the RGB components of the detected image are compared with the temporary average extracted from the previous instants, which means that detection is not carried out using an absolute value. On the other hand, a neural network is used as a detector that through supervised training manages to distinguish the variations due to the transmission of those due to ambient light.
URI: http://hdl.handle.net/10553/106131
Colección:Ponencias
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actualizado el 13-jul-2024

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