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.
Elsabrouty, M. (2007). AN OLD WORKFRAME FOR A NEW PROBLEM: A CLASSICAL MODEL FOR UNSUPERVISED ADAPTIVE FILTERING. International Conference on Aerospace Sciences and Aviation Technology, 12(ASAT Conference, 29-31 May 2007), 1-10. doi: 10.21608/asat.2007.24130
MLA
M. Elsabrouty. "AN OLD WORKFRAME FOR A NEW PROBLEM: A CLASSICAL MODEL FOR UNSUPERVISED ADAPTIVE FILTERING". International Conference on Aerospace Sciences and Aviation Technology, 12, ASAT Conference, 29-31 May 2007, 2007, 1-10. doi: 10.21608/asat.2007.24130
HARVARD
Elsabrouty, M. (2007). 'AN OLD WORKFRAME FOR A NEW PROBLEM: A CLASSICAL MODEL FOR UNSUPERVISED ADAPTIVE FILTERING', International Conference on Aerospace Sciences and Aviation Technology, 12(ASAT Conference, 29-31 May 2007), pp. 1-10. doi: 10.21608/asat.2007.24130
VANCOUVER
Elsabrouty, M. AN OLD WORKFRAME FOR A NEW PROBLEM: A CLASSICAL MODEL FOR UNSUPERVISED ADAPTIVE FILTERING. International Conference on Aerospace Sciences and Aviation Technology, 2007; 12(ASAT Conference, 29-31 May 2007): 1-10. doi: 10.21608/asat.2007.24130
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