This paper proposes a very fast method for blindly initial-
izing a nonlinear mapping which transforms a sum of random variables.
The method provides a surprisingly good approximation even when the
basic assumption is not fully satis¯ed. The method can been used success-
fully for initializing nonlinearity in post-nonlinear ...»»»»
This paper proposes a very fast method for blindly initial-
izing a nonlinear mapping which transforms a sum of random variables.
The method provides a surprisingly good approximation even when the
basic assumption is not fully satis¯ed. The method can been used success-
fully for initializing nonlinearity in post-nonlinear mixtures or in Wiener
system inversion, for improving algorithm speed and convergence.^^^^
Tipo de documento:
Conferencia
Derechos:
(c) Springer (The original publication is available at www.springerlink.com)
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Citación Bibliográfica:
SOLÉ CASALS, J., JUTTEN, C. and PHAM, D.T., 2003. Initialisation of nonlinearities for PNL and Wiener systems inversion, J. MIRA and J.R. ALVAREZ, eds. In: Artificial Neural Nets Problem Solving Methods, Pt Ii; LECTURE NOTES IN COMPUTER SCIENCE; 7th International Work Conference on Artificial and Natural Neural Networks, JUN 03-06, 2003 2003, SPRINGER-VERLAG BERLIN, pp. 225-232.