Li, Yan ORCID: https://orcid.org/0000-0002-4694-4926 and Powers, David and Peach, James
(2001)
Comparison of blind source separation algorithms.
In: WSES International Conference on Neural Networks and Applications 2001, 11-15 Feb 2001, Tenerife, Spain.
Abstract
A set of experiments are designed to evaluate and compare the performances of three well known blind source separation algorithms in this paper. The specific algorithms studied are two group of neural networks algorithms, Bell and Sejnowski's infomax algorithm and Hyvärinen's fixed-point family, and J. F. Cardoso's joint approxomate diagonalization of eigen-matrices algorithm. In this paper, the algorithms are quantitively evaluated and compared using the three measures, MATLAB flops (floating point operations), the difference between the mixing and separating matrices and the signal-to-noise ratios of the separated signals in this paper.
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