Title :
Convergence of the iterative Hammerstein system identification algorithm
Author :
Bai, Er-Wei ; Li, Duan
Author_Institution :
Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA, USA
Abstract :
It is shown that the iterative algorithm with normalization is convergent in general. Moreover, the convergence takes place in one step (two least squares iterations) for FIR Hammerstein models with i.i.d. inputs.
Keywords :
cascade systems; convergence of numerical methods; identification; iterative methods; least squares approximations; nonlinear control systems; FIR Hammerstein models; convergence; i.i.d. inputs; iterative Hammerstein system identification algorithm; least squares iterations; normalization; Cities and towns; Convergence; Finite impulse response filter; Frequency domain analysis; Iterative algorithms; Iterative methods; Least squares methods; Nonlinear equations; Stochastic processes; System identification;
Conference_Titel :
Decision and Control, 2004. CDC. 43rd IEEE Conference on
Print_ISBN :
0-7803-8682-5
DOI :
10.1109/CDC.2004.1429341
