Title :
A RBF equalizer using fast clustering algorithm
Author :
Kim, Jung-Su ; Sihn, Bong-Sik ; Chong, Jong-Wha
Author_Institution :
CAD & Commun. Circuit Lab., Han Yang Univ., Seoul, South Korea
fDate :
Oct. 29 2000-Nov. 1 2000
Abstract :
A RBF (radial basis function) network has been used in digital communication channel equalization for its identical structure to the optimal Bayesian symbol by symbol decision equalizer. The most important problem in the equalization using RBF is the fast searching of the correct centers (channel states). The k-means clustering algorithm has been used to find the desired channel states. In this paper, the problem can be transformed into finding the representative centers suitable for channel states using the interrelation among the elements of the center set. Computer simulation results show its fast convergence speed and less training iteration than equalization using the traditional k-means clustering algorithm.
Keywords :
convergence of numerical methods; digital communication; equalisers; iterative methods; pattern clustering; radial basis function networks; telecommunication computing; RBF equalizer; channel states; convergence speed; digital communication channel equalization; fast clustering algorithm; k-means clustering algorithm; radial basis function; searching; training iteration; Additive white noise; Bayesian methods; Binary sequences; Clustering algorithms; Data communication; Decision feedback equalizers; Delay estimation; Digital communication; Gaussian noise; Radial basis function networks;
Conference_Titel :
Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-6514-3
DOI :
10.1109/ACSSC.2000.910662