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• W2102029306 abstract "The aim of this work is to present a nonlinear extension to Sanger's generalized Hebbian learning algorithm for complex-valued signal processing by neural networks. A possible choice of the involved nonlinearity is discussed by recalling the Sudjianto-Hassoun interpretation of nonlinear Hebbian learning. An extension of this interpretation to the complex-valued case leads to a Rayleigh nonlinearity, that allows for separating mixed independent complex-valued circular source signals." @default.
• W2102029306 created "2016-06-24" @default.
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• W2102029306 date "2003-04-01" @default.
• W2102029306 modified "2023-09-27" @default.
• W2102029306 title "Extended hebbian learning for blind separation of complex-valued sources" @default.
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• W2102029306 doi "https://doi.org/10.1109/tcsii.2003.810486" @default.
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