DocumentCode :
2427257
Title :
Computational aspects of adaptive radial basis function equalizer design
Author :
Patra, Sarat Kumar ; Mulgrew, Bernard
Author_Institution :
Dept. of Electr. Eng., Edinburgh Univ., UK
Volume :
1
fYear :
1997
fDate :
9-12 Jun 1997
Firstpage :
521
Abstract :
This paper investigates the computational aspects of radial basis function (RBF) equalizers. In an RBF implementation of the Bayesian equalizer the RBF centers are placed at equalizer channel states and the output layer weights are adjusted to +1/-1. Here we propose an RBF equalizer with scalar centers which can implement the Bayesian decision function. The proposed RBF equalizer provides lower computational complexity compared to the reported RBF equalizers and can efficiently employ subset center selection for computing the decision function resulting in a substantial reduction in computational complexity
Keywords :
Bayes methods; adaptive equalisers; computational complexity; Bayesian decision function; adaptive radial basis function equalizer; channel states; computational complexity; design; scalar centers; subset center selection; AWGN; Additive white noise; Bayesian methods; Delay; Dispersion; Equalizers; Equations; Gaussian noise; Intersymbol interference; Signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1997. ISCAS '97., Proceedings of 1997 IEEE International Symposium on
Print_ISBN :
0-7803-3583-X
Type :
conf
DOI :
10.1109/ISCAS.1997.608793
Filename :
608793
Link To Document :
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