DocumentCode
2128992
Title
Identification of bilinear systems using Bayesian inference
Author
Meddeb, Souad ; Tourneret, Jean Yves ; Castanie, Francis
Author_Institution
ENSEEIHT/GAPSE, Toulouse, France
Volume
3
fYear
1998
fDate
12-15 May 1998
Firstpage
1609
Abstract
A large class of nonlinear phenomena can be described using bilinear systems. Such systems are very attractive since they usually require few parameters, to approximate most nonlinearities (compared to other systems). This paper addresses the problems of bilinear system identicalness using Bayesian inference. The Gibbs sampler is used to estimate the bilinear system parameters, from measurements of the system input and output signals
Keywords
Bayes methods; Markov processes; Monte Carlo methods; bilinear systems; discrete time systems; inference mechanisms; parameter estimation; signal sampling; Bayesian inference; Gibbs sampler; bilinear systems; identicalness; identification; nonlinear phenomena; nonlinearities; system input; system output; Bayesian methods; Earthquakes; Explosions; Feedback; Kernel; Nonlinear systems; Parameter estimation; Polynomials; Seismology; Signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location
Seattle, WA
ISSN
1520-6149
Print_ISBN
0-7803-4428-6
Type
conf
DOI
10.1109/ICASSP.1998.681761
Filename
681761
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