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Nonlinear identification in the presence of correlated noise using a Hammerstein model

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3 Author(s)
Haist, N. ; University of Toronto, Toronto, Canada ; Chang, F. ; Luus, R.

A simple iterative technique for the estimation of parameters in a Hammerstein model is developed for the case when noise in the output data is correlated. Asymptotically unbiased estimates are obtained rapidly by employing a systematic procedure for the determination of a scalar stepping factor at each iteration.

Published in:

Automatic Control, IEEE Transactions on  (Volume:18 ,  Issue: 5 )