Title :
General framework for asymptotic properties of generalized weighted nonlinear least-squares estimators with deterministic and stochastic weighting
Author :
Vandersteen, Gerd ; Van Hamme, Hugo ; Pintelon, Rik
Author_Institution :
Vrije Univ., Brussels, Belgium
fDate :
10/1/1996 12:00:00 AM
Abstract :
This paper studies the asymptotic properties (strong consistency, convergence rate, asymptotic normality) of a generalized weighted nonlinear least-squares estimator under weak noise assumptions. Both deterministic and stochastic weighting are handled and the presence of model errors is considered. For particular models, estimators, and noise assumptions the general framework boils down to known time and frequency-domain estimators
Keywords :
convergence of numerical methods; frequency-domain analysis; least squares approximations; parameter estimation; stochastic processes; time-domain analysis; asymptotic normality; convergence rate; deterministic weighting; frequency-domain analysis; identification; model errors; parameter estimation; stochastic weighting; strong consistency; time-domain analysis; weak noise; weighted nonlinear least-squares estimators; Convergence; Cost function; Frequency estimation; Least squares approximation; Maximum likelihood estimation; Parameter estimation; Signal processing; Signal to noise ratio; Stochastic processes; Stochastic resonance;
Journal_Title :
Automatic Control, IEEE Transactions on
