AN OLD WORKFRAME FOR A NEW PROBLEM: A CLASSICAL MODEL FOR UNSUPERVISED ADAPTIVE FILTERING | ||||
| International Conference on Aerospace Sciences and Aviation Technology | ||||
| Article 111, Volume 12, ASAT Conference, 29-31 May 2007, May 2007, Page 1-10 PDF (132.8 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/asat.2007.24130 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| M. Elsabrouty | ||||
| Faculty of Information and Engineering Technology, The German University in Cairo. | ||||
| Abstract | ||||
| A classical adaptive filtering model of the problem of instantaneous blind signal separation, or what is formally known as unsupervised adaptive filtering is presented. This classical form helps understanding the well-known superior behaviour of the natural gradient solution to the blind separation problem. A new RLS-based algorithm is developed using this classical model. The algorithm provides improved on-line separation speed under the same steady state error compared to the natural gradient algorithm without requiring pre-whitening. | ||||
| Keywords | ||||
| Blind Signal Separation; Natural Gradient; Recursive Least Square; Unsupervised Adaptive Filtering | ||||
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