DocumentCode
1847275
Title
Identification of Wiener models with data pre-filtering
Author
Chou, C.T. ; Verhaegen, M.
Author_Institution
Dept. of Electr. Eng., Delft Univ. of Technol., Netherlands
Volume
1
fYear
1999
fDate
1999
Firstpage
604
Abstract
Data pre-filtering, i.e. filtering both the input and output data with an identical scalar filter, is a useful tool in the identification of linear time-invariant systems but is generally not applicable to nonlinear system identification. We show that, if the correlation approach is used to identify Wiener models, which are nonlinear, pre-filtering can be used if the input excitation is Gaussian
Keywords
Gaussian distribution; correlation methods; filtering theory; identification; matrix algebra; Gaussian input excitation; Wiener models; correlation approach; data pre-filtering; identical scalar filter; Filtering; Finite impulse response filter; Linear systems; Nonlinear filters; Nonlinear systems; Physics; Signal mapping; Signal processing; State-space methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1999. Proceedings of the 38th IEEE Conference on
Conference_Location
Phoenix, AZ
ISSN
0191-2216
Print_ISBN
0-7803-5250-5
Type
conf
DOI
10.1109/CDC.1999.832850
Filename
832850
Link To Document