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
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;
Conference_Titel :
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-7061-9
DOI :
10.1109/.2001.980965
