Complex independent component analysis by nonlinear generalized Hebbian learning with Rayleigh nonlinearity
Acoustics, Speech, and Signal Processing, IEEE International Conference on (1999)
Phoenix, AZ, USA
Mar. 15, 1999 to Mar. 19, 1999
E. Pomponi , Dipt. di Elettronica e Autom., Ancona Univ., Italy
This paper presents a non-linear extension of the Sanger's (1989) generalized Hebbian algorithm to the processing of complex-valued data. A possible choice of the involved nonlinearity is discussed recalling the Sudjianto-Hassoun (1994) interpretation of the nonlinear Hebbian learning. Extension of this interpretation to the complex case leads to a nonlinearity called the Rayleigh function, which allows for separating mixed independent complex-valued source signals.
F. Piazza, E. Pomponi and S. Fiori, "Complex independent component analysis by nonlinear generalized Hebbian learning with Rayleigh nonlinearity," 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99(ICASSP), Phoenix, AZ, USA, 1999, pp. 1077-1080.