DocumentCode
2953667
Title
Blind equalization Using ν- support vector regressor for constant modulus signals
Author
Liu, Feng ; An, Hu-cheng ; Li, Jia-ming ; Ge, Lin-dong
Author_Institution
Inf. Sci. & Technol. Inst., Zhengzhou
fYear
2008
fDate
1-8 June 2008
Firstpage
161
Lastpage
164
Abstract
The support vector machine has been recently developed for blind equalization of constant modulus signals. In this paper we propose to use a v-support vector regressor (nu-SVR) for blindly equalizing multipath channels because of the high generalization ability of the SVR for short burst sequences. A weighted least square procedure is presented for solving the blind nu-SVR equalizer. The performance of the proposed algorithm is analyzed by means of computer simulations.
Keywords
blind equalisers; blind source separation; least squares approximations; multipath channels; regression analysis; support vector machines; telecommunication computing; blind equalizing multipath channel; constant modulus signal; short burst sequence; support vector machine; support vector regression; weighted least square procedure; Blind equalizers; Convergence; Intersymbol interference; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4633783
Filename
4633783
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