Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/69882
Título: Equalizer for an IR-wireless LAN using RBF neural networks
Autores/as: Pérez-Jiménez, R. 
Martín-Bernardo, J.
Melián, V. M. 
Ruiz-Alzola, J. 
Betancor, M. J.
Clasificación UNESCO: 3325 Tecnología de las telecomunicaciones
Palabras clave: Wireless LAN
Fecha de publicación: 1993
Editor/a: Institute of Electrical and Electronics Engineers (IEEE) 
Publicación seriada: Conference on Local Computer Networks 
Conferencia: 18th Conference on Local Computer Networks, LCN 1993 
Resumen: The application of a RBF (radial basis function) neural network to an adaptive equalizer at the receiver of a wireless IR-LAN is considered. Fixing the decision threshold and classifying the received binary signals are the main functions of the RBF. The general problem of equalization binary signals, passed through a dispersive channel and corrupted with noise, is briefly described. The characterization of the receiver and the effects of both Gaussian and shot noise over the signals are studied. A possible architecture for the equalizer and a comparison with other classical structures (multilayer perceptron and linear transversal equalizer), as well as simulation results are given. Considerations about the way of reducing computational complexity are proposed.
URI: http://hdl.handle.net/10553/69882
ISBN: 0-8186-4510-5
ISSN: 0742-1303
DOI: 10.1109/LCN.1993.591261
Fuente: 18th Conference on Local Computer Networks, Minneapolis, MN, USA, 1993, p. 461-466
Colección:Actas de congresos
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