Title :
An on-line algorithm for blind source extraction based on nonlinear prediction approach
Author :
Mandic, Danilo P. ; Cichocki, Andrzej ; Manmontri, Uttachai
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. London, UK
Abstract :
A gradient descent based on-line algorithm for blind source extraction (BSE) of instantaneous signal mixtures is proposed. This algorithm is derived by utilising a nonlinear adaptive filter in a structure that consists of an extraction and prediction module. By exploiting the predictability property of a signal from the mixture, source signals are extracted based on the order of the nonlinear adaptive predictor. To improve the convergence of the basic algorithm, it is further globally normalised based on the minimisation of the a posteriori prediction error. Next, the algorithm is made fully adaptive to compensate for the independence and other assumptions in its derivation. Two examples are presented to illustrate the performance of the algorithms.
Keywords :
adaptive filters; blind source separation; gradient methods; nonlinear filters; prediction theory; blind source extraction; nonlinear adaptive filter; nonlinear adaptive predictor; online algorithm; predictability property; Adaptive filters; Biomedical signal processing; Blind source separation; Convergence; Educational institutions; Independent component analysis; Predictive models; Signal processing; Signal processing algorithms; Source separation;
Conference_Titel :
Neural Networks for Signal Processing, 2003. NNSP'03. 2003 IEEE 13th Workshop on
Print_ISBN :
0-7803-8177-7
DOI :
10.1109/NNSP.2003.1318042