Title :
Neural blind separation of complex sources by extended APEX algorithm (EAPEX)
Author :
Fiori, Sirnone ; Uncini, Aurelio ; Piazza, Francesco
Author_Institution :
Dipt. di Elettronica e Autom., Ancona Univ., Italy
Abstract :
Blind Source Separation by non-classical (non-quadratic) neural Principal Component Analysis has been investigated by several papers over the recent years, even if particular attention has been paid to the real-valued sources case. The aim of this work is to present an extension of the Kung-Diamantaras´ APEX learning rule to non-quadratic complex optimization, and to show the new approach allows blind separation of complex-valued source signals from their linear mixtures
Keywords :
Hebbian learning; neural nets; optimisation; principal component analysis; signal processing; APEX learning rule; EAPEX; complex sources; complex-valued source signals; extended APEX algorithm; linear mixtures; neural blind separation; nonquadratic Hebbian learning; nonquadratic complex optimization; Blind source separation; Ear; Equations; Independent component analysis; Lagrangian functions; Neural networks; Principal component analysis; Source separation;
Conference_Titel :
Circuits and Systems, 1999. ISCAS '99. Proceedings of the 1999 IEEE International Symposium on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-5471-0
DOI :
10.1109/ISCAS.1999.777650
