DocumentCode
1356070
Title
A solution to linear estimation problems using approximate Karhunen-Loeve expansions
Author
Navarro-Moreno, Jesís ; Ruiz-Molina, Juan Carlos ; Valderrama, Mariano J.
Author_Institution
Dept. of Stat. & Oper. Res., Univ. of Jaen, Spain
Volume
46
Issue
4
fYear
2000
fDate
7/1/2000 12:00:00 AM
Firstpage
1677
Lastpage
1682
Abstract
An explicit and efficiently calculable solution is presented to the problem of linear least-mean-squared-error estimation of a signal process based upon noisy observations that is valid for finite intervals. This approach is based on approximate Karhunen-Loeve expansions of a stochastic process and can be extended to estimate a linear operation, in the sense of the quadratic mean, of the signal process
Keywords
Karhunen-Loeve transforms; least mean squares methods; noise; signal representation; stochastic processes; approximate Karhunen-Loeve expansions; finite intervals; linear estimation problems; linear least-mean-squared-error estimation; linear operation; noisy observations; quadratic mean; signal process; stochastic process; Decorrelation; Eigenvalues and eigenfunctions; Filters; Operations research; Random processes; Random variables; Signal processing; Statistics; Stochastic processes;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.850715
Filename
850715
Link To Document