Title :
On the worst-case performance of the least squares algorithm
Author :
Akçay, Huseyin ; Khargonekar, Pramod P.
Author_Institution :
Dept. of Mech. Eng., Michigan Univ., Ann Arbor, MI, USA
Abstract :
The worst case performance of the least squares parametric system identification algorithm is analyzed assuming the noise is a bounded signal. A bound on the worst-case parameter estimation error is derived. This bound shows that the worst-case parameter estimation error decreases to zero as the bound on the noise is decreased to zero
Keywords :
identification; least squares approximations; noise; parameter estimation; bounded signal; least squares algorithm; least squares parametric system identification; noise; parameter estimation error; worst-case performance; Books; Gaussian noise; Least squares approximation; Least squares methods; Noise robustness; Parameter estimation; Signal processing; Stochastic resonance; System identification; Transfer functions;
Conference_Titel :
Decision and Control, 1993., Proceedings of the 32nd IEEE Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-1298-8
DOI :
10.1109/CDC.1993.325565
