DocumentCode
2197442
Title
A blind approach to Hammerstein model identification
Author
Bai, Er-Wei ; Fu, Minyue
Author_Institution
Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA, USA
Volume
5
fYear
2001
fDate
2001
Firstpage
4794
Abstract
Discusses discrete Hammerstein model identification using a blind system identification approach. By sampling faster at the output for the sampled Hammerstein systems, it is shown that identification of the linear part can be achieved based only on the output measurements that makes Hammerstein model identification possible without knowing the structure of the nonlinearity and the internal variable. The fundamental identifiability problem is solved and several schemes are presented
Keywords
convergence; identification; nonlinear systems; sampled data systems; blind system identification approach; convergence analysis; discrete Hammerstein model identification; nonlinear system; sampled Hammerstein systems; sampled linear system; Australia; Cities and towns; Least squares methods; Linear systems; Noise figure; Noise measurement; Sampling methods; System identification; Transfer functions;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-7061-9
Type
conf
DOI
10.1109/.2001.980965
Filename
980965
Link To Document