DocumentCode :
303412
Title :
Neural network identification of digital satellite channels: the adaptive nonlinear enhancer
Author :
Ibnkahla, Mohamed ; Castanie, Francis
Author_Institution :
ENSEEIHT, Toulouse, France
Volume :
3
fYear :
1996
fDate :
3-6 Jun 1996
Firstpage :
1628
Abstract :
This paper presents a neural network approach for modelling satellite communication channels which are equipped with nonlinear devices (travelling wave tubes (TWT)). The model is based upon the use of multilayer neural networks (MLNN) which are trained with the back propagation (BP) algorithm. It is shown from simulation results that the TWT characteristic can be extracted by the neural net model, as well as the linear filters included in the channel. The learning process is performed by using the channel input and output signals. The neural network model works as an adaptive nonlinear enhancer
Keywords :
backpropagation; digital radio; filtering theory; multilayer perceptrons; satellite communication; telecommunication channels; telecommunication computing; travelling wave tubes; TWT; adaptive nonlinear enhancer; digital satellite channels; multilayer neural networks; neural network identification; satellite communication channels; travelling wave tubes; Adaptive signal processing; Bandwidth; Iterative algorithms; Multi-layer neural network; Neural networks; Nonlinear filters; Phase distortion; Satellite broadcasting; Satellite communication; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1996., IEEE International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-3210-5
Type :
conf
DOI :
10.1109/ICNN.1996.549144
Filename :
549144
Link To Document :
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