Title :
Random sequences optimal estimation by using regression and wavelets
Author :
Amosov, Oleg S. ; Amosova, Liudmila N.
Author_Institution :
Amur State Univ. of Humanities & Pedagogy, Komsomolsk-on-Amur, Russia
Abstract :
This paper is concerned with random sequences optimal estimation by using regression with unknown type of the regression function and wavelets. The regression and wavelet based estimation algorithms are offered. It is shown that the Bayesian and the alternative regression and wavelet based algorithms provide estimates with the close accuracy. Two examples for linear and nonlinear filtering and prediction problems are considered.
Keywords :
Bayes methods; nonlinear filters; prediction theory; random sequences; regression analysis; wavelet transforms; Bayesian; nonlinear filtering; prediction problem; random sequence optimal estimation; regression function; wavelet based estimation; Automatic control; Bayesian methods; Filtering; Filters; Fuzzy systems; Neural networks; Random sequences; Signal processing algorithms; Smoothing methods; State estimation;
Conference_Titel :
Control and Automation, 2009. ICCA 2009. IEEE International Conference on
Conference_Location :
Christchurch
Print_ISBN :
978-1-4244-4706-0
Electronic_ISBN :
978-1-4244-4707-7
DOI :
10.1109/ICCA.2009.5410327
