|Title:||Equalizer for an IR-wireless LAN using RBF neural networks||Authors:||Pérez-Jiménez, R.
Melián, V. M.
Betancor, M. J.
|UNESCO Clasification:||3325 Tecnología de las telecomunicaciones||Keywords:||Wireless LAN||Issue Date:||1993||Publisher:||Institute of Electrical and Electronics Engineers (IEEE)||Journal:||Conference on Local Computer Networks||Conference:||18th Conference on Local Computer Networks, LCN 1993||Abstract:||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||Source:||18th Conference on Local Computer Networks, Minneapolis, MN, USA, 1993, p. 461-466|
|Appears in Collections:||Actas de congresos|
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