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A Channel Equalization Algorithm Using Neural Network Based Data Least Squares  

Lim, Jun-Seok (Department of Electronics Engineering Sejong University)
Pyeon, Yong-Kuk (Gangwon Provincial College)
Publication Information
The Journal of the Acoustical Society of Korea / v.26, no.2E, 2007 , pp. 63-68 More about this Journal
Abstract
Using the neural network model for oriented principal component analysis (OPCA), we propose a solution to the data least squares (DLS) problem, in which the error is assumed to lie in the data matrix only. In this paper, we applied this neural network model to channel equalization. Simulations show that the neural network based DLS outperforms ordinary least squares in channel equalization problems.
Keywords
Data Least Square Method; Oriented Principal Component Analysis; Equalization;
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  • Reference
1 C.E. Davila, 'Line Search Algorithm for Adaptive Filtering,' IEEE Trans, Signal Processing, 42, 2490-2494, 1994
2 K.I. Diamantaras and S.Y. Kung, Principal Component Neural Networks: Theory and Applications, (Wiley, 1996), PP. 186-202
3 R.D. DeGroat and E, M. Dowling, 'The Data Least Squares and Channel Equalization,' IEEE Trans. Signal Processing, 41, 407-411, 1993   DOI   ScienceOn
4 E.F. Deprettere, editor, SVD and Signal Processing, (Elsevier Science Publishers, New York, 1973), pp, 209-232
5 G. H. Golub and C. F. Van Loan, 'An analysis of the total least squares problem,' SIAMJ, Num, Anal., 17, 883- 893, 1980   DOI   ScienceOn
6 Cha, I. and S.A. Kassam, 'Channel equalization using adaptive complex radial basis function networks,' IEEE J. Sel. Area, Comm. 13, 122-131, 1995   DOI   ScienceOn