Title :
A flexible Blind source recovery in complex nonlinear environment
Author :
Vigliano, D. ; Scarpiniti, M. ; Parisi, R. ; Uncini, A.
Author_Institution :
INFOCOM Dept., Universita degli Studi di Roma "La Sapienza", Rome
Abstract :
In this paper the source recovery of nonlinear mixtures in the complex domain is addressed by an independent component analysis (ICA) approach. Extending the well-known real PNL mixtures, source recovery is performed by a complex INFOMAX approach. Nonlinear complex functions involved in the learning process are realized by pairs of spline neurons called "splitting functions", working on the real and the imaginary part of the signal respectively. A simple adaptation algorithm is derived and some experimental results that demonstrate the effectiveness of the proposed method are shown
Keywords :
blind source separation; independent component analysis; learning (artificial intelligence); neural nets; splines (mathematics); INFOMAX approach; blind source recovery; complex nonlinear environment; independent component analysis; learning process; nonlinear mixtures; spline neurons; splitting functions; Biomedical signal processing; Blind source separation; Independent component analysis; Intelligent control; Neurons; Nonlinear distortion; Signal processing; Signal processing algorithms; Source separation; Spline;
Conference_Titel :
Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006 IEEE
Conference_Location :
Munich
Print_ISBN :
0-7803-9797-5
Electronic_ISBN :
0-7803-9797-5
DOI :
10.1109/CACSD-CCA-ISIC.2006.4777126