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سند علمی

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

Eraldo Pomponi, Simone G. O. Fiori, Francesco Piazza

چکیده

The aim of this paper is to present a non-linear extension of the Sanger’s Generalized Hebbian Algorithm to the processing of complex-valued data. A possible choice of the involved non-linearity is discussed recalling the Sudjianto-Hassoun interpretation of the nonlinear Hebbian learning. Extension of this interpretation to the complex case leads to a nonlinearity called Rayleigh function, which allows for separating mixed independent complex-valued source signals.

اسناد مشابه

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