Title :
A comparison of least squares algorithms for estimating Markov parameters
Author :
Fledderjohn, M.S. ; Holzel, M.S. ; Palanthandalam-Madapusi, Harish J. ; Fuentes, R.J. ; Bernstein, D.S.
Author_Institution :
Univ. of Michigan, Ann Arbor, MI, USA
fDate :
June 30 2010-July 2 2010
Abstract :
The purpose of this work is to compare model structures and identification algorithms for estimating Markov parameters in the presence of uncorrelated and correlated input, process, and output noise. We consider several least-squares variants with ARX and μ-Markov model structures, which are compared with white noise identification signals.
Keywords :
Markov processes; autoregressive processes; least squares approximations; parameter estimation; signal processing; white noise; μ-Markov model structure; ARX model; Markov parameter estimation; identification algorithm; least squares algorithm; output noise; white noise identification signal; Aerospace engineering; Least squares approximation; Least squares methods; Linear systems; Noise figure; Parameter estimation; Signal processing; Signal to noise ratio; State-space methods; White noise;
Conference_Titel :
American Control Conference (ACC), 2010
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-7426-4
DOI :
10.1109/ACC.2010.5530673
