Comparison of blind source separation algorithms
Paper
Paper/Presentation Title | Comparison of blind source separation algorithms |
---|---|
Presentation Type | Paper |
Authors | Li, Yan (Author), Powers, David (Author) and Peach, James (Author) |
Editors | Mastorakis, Nikos E. |
Journal or Proceedings Title | Advances in Neural Networks and Applications |
Number of Pages | 6 |
Year | 2001 |
Place of Publication | Greece |
ISBN | 9608052262 |
Web Address (URL) of Paper | http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.138.4896&rep=rep1&type=pdf |
Conference/Event | WSES International Conference on Neural Networks and Applications 2001 |
Event Details | WSES International Conference on Neural Networks and Applications 2001 Event Date 11 to end of 15 Feb 2001 Event Location 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. |
Keywords | blind souce separation; fixed-point algorithm; information maximisation; JADE |
ANZSRC Field of Research 2020 | 520203. Cognitive neuroscience |
469999. Other information and computing sciences not elsewhere classified | |
461399. Theory of computation not elsewhere classified | |
Public Notes | FROM: Proceedings of the Conference on Neural Networks and Applications, Tenerife, Spain 2001 |
Byline Affiliations | Department of Mathematics and Computing |
Flinders University | |
Institution of Origin | University of Southern Queensland |
Book Title | Advances in Neural Networks and Applications |
https://research.usq.edu.au/item/q0408/comparison-of-blind-source-separation-algorithms
589
total views6
total downloads9
views this month0
downloads this month