Title :
Channel equalization by finite mixtures and the EM algorithm
Author_Institution :
Dept. of Comput. Sci., Chinese Univ. of Hong Kong, Shatin, Hong Kong
fDate :
31 Aug-2 Sep 1995
Abstract :
The model of finite mixtures and the EM learning algorithm have been applied to the task of channel equalization in communication problems for the channels that may vary its properties between a number of different modes. Computer experiments have also been given to show that the proposed approach work well with a promising potential for applications
Keywords :
equalisers; telecommunication channels; unsupervised learning; EM algorithm; EM learning algorithm; channel equalization; communication problems; computer experiments; finite mixtures; parametric model; unsupervised learning models; Adaptive equalizers; Application software; Communication channels; Computer science; Least squares approximation; Parametric statistics; Switches; Transfer functions; Transversal filters; Unsupervised learning;
Conference_Titel :
Neural Networks for Signal Processing [1995] V. Proceedings of the 1995 IEEE Workshop
Conference_Location :
Cambridge, MA
Print_ISBN :
0-7803-2739-X
DOI :
10.1109/NNSP.1995.514935
