Inversion of a nonlinear communication channel by kriging

Author

Costa, J.P. ; Pronzato, Luc ; Thierry, E.

Author_Institution

Lab. I3S, CNRS-UNSA, Biot, France

Volume

3

fYear

1999

fDate

1999

Firstpage

1585

Abstract

We consider a problem of nonlinear system-inversion, with unknown underlying model structure. Classical parametric behavioural models (Volterra and NARMAX models) involve a lot of parameters, which are difficult to estimate from short training sequences. A similar difficulty is encountered when methods based on neural networks are used. We suggest in this paper to use a semi-parametric approach called kriging. We show on an example that good performances are obtained for short training sequences

Keywords

covariance matrices; filtering theory; inverse problems; nonlinear systems; optimisation; prediction theory; statistical analysis; telecommunication channels; jamming; kriging; nonlinear communication channel; nonlinear system-inversion; optimisation; parametric behavioural models; radial basic function; semi-parametric approach; training sequences; Autoregressive processes; Communication channels; Covariance matrix; Neural networks; Nonlinear systems; Polynomials; Predictive models; Random processes; Signal processing; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Circuits and Systems, 1999. Proceedings of ICECS '99. The 6th IEEE International Conference on

Conference_Location

Pafos

Print_ISBN

0-7803-5682-9

Type

conf

DOI

10.1109/ICECS.1999.814475

Filename

814475