DocumentCode
914667
Title
Estimation with finite memory
Author
Roberts, Richard A. ; Tooley, John R.
Volume
16
Issue
6
fYear
1970
fDate
11/1/1970 12:00:00 AM
Firstpage
685
Lastpage
691
Abstract
A finite-state model for sequential minimum-mean-square-error estimation of a random variable in additive noise is analyzed to determine the dependence of optimum performance and structure on the memory size of the estimator. Necessary conditions for determining the structure of the optimum finite-state estimator are derived for arbitrary statistics. Numerical results are presented for Gaussian statistics. The performance of several different estimators is used to show the trade-off one may obtain between memory size, observation quality, and number of observations.
Keywords
Finite-memory methods; Sequential estimation; Additive noise; Constraint theory; Degradation; Estimation theory; Instruments; Memory management; Performance analysis; Random variables; Statistics;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.1970.1054536
Filename
1054536
Link To Document