Complex independent component analysis by nonlinear generalized Hebbian learning with Rayleigh nonlinearity

  • Authors:

  • E. Pomponi;S. Fiori;F. Piazza

  • Affiliations:

  • Dipt. di Elettronica e Autom., Ancona Univ., Italy;-;-

  • Venue:
  • ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
  • Year:
  • 1999

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Abstract

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.