Title :
Relative Newton method for signal separation
Author :
Zibulevsky, Michael
Author_Institution :
Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel
Abstract :
The presented relative Newton method for quasi-maximum likelihood blind source separation significantly outperforms the natural gradient descent in batch mode. The structure of the corresponding Hessian matrix allows its fast inversion without assembling. Experiments with sparsely representable signals demonstrate super-efficient separation. More experiments with natural images are presented elsewhere (http://ie.technion.ac.il/∼mcib/).
Keywords :
Hessian matrices; Newton method; blind source separation; optimisation; Hessian matrix; natural gradient descent; natural images; quasi-maximum likelihood blind source separation; relative Newton method; relative optimization; signal separation; sparse signals; Assembly; Blind source separation; Convergence; Gradient methods; Matrix converters; Minimization methods; Newton method; Probability density function; Source separation; Sparse matrices;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
Print_ISBN :
0-7803-7663-3
DOI :
10.1109/ICASSP.2003.1199860
