A neural network based data least squares algorithm for channel equalization

Authors:
Jun-Seok Lim
Affiliations:
Dept. of Electronics Eng., Sejong University, Seoul, Korea
Venue:
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Year:
2007

Citing 3
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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 DLS outperforms ordinary least squares in channel equalization problems.