DSpace Repository

Initialisation of Nonlinearities for PNL and Wiener systems Inversion

Initialisation of Nonlinearities for PNL and Wiener systems Inversion
 
Solé-Casals, Jordi ; Jutten, Christian ; Pham, Dinh-Tuan
2003

Files in this item

Icon
Name: artconlli_a2003_sole_casals_initialisation_nonlinearities.pdf
Size: 503.3Kb
Format: PDF
Enllaç permanent: http://hdl.handle.net/10854/2091
 

Abstract

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.^^^^

Type:

Conference object

Rights:

 
(c) Springer (The original publication is available at www.springerlink.com)
 
Tots els drets reservats
 

Citation:

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.