Title :
A recursive randomized EM-algorithm for estimation under quantization error
Author :
Finesso, Lorenzo ; Gerencs, Laszlo ; Kmecs, Ildiko
Author_Institution :
LADSEB, CNR, Padova, Italy
Abstract :
The purpose of the paper is to formulate and study the problem of system identification with Gaussian noise and quantized observations. The motivation for this research is the estimation of quantized Gaussian ARMA-processes, but in the paper we focus on Gaussian linear regression. The main result is the development of a randomized EM-method for the effective solution of the likelihood equation and derivation of an online version in the simplest case
Keywords :
Gaussian noise; approximation theory; autoregressive moving average processes; integral equations; maximum likelihood estimation; observers; recursive estimation; Gaussian linear regression; Gaussian noise; likelihood equation; quantization error; quantized observations; recursive randomized EM-algorithm; system identification; Automation; Biomedical computing; Biomedical engineering; Equations; Estimation error; Gaussian noise; Linear regression; Maximum likelihood estimation; Quantization; Recursive estimation;
Conference_Titel :
American Control Conference, 2000. Proceedings of the 2000
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-5519-9
DOI :
10.1109/ACC.2000.876606
