DocumentCode
916329
Title
Estimation using subjective knowledge with tracking applications
Author
Popoli, Robert ; Mendel, Jerry
Author_Institution
Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA
Volume
29
Issue
3
fYear
1993
fDate
7/1/1993 12:00:00 AM
Firstpage
610
Lastpage
623
Abstract
Within the framework of classical estimation theory, there is no technically legitimate way to utilize knowledge that cannot be codified by either deterministic or strict probability models. The authors introduce a theoretically defensible approach called coordinated objective/subjective estimation (COSE) for the simultaneous incorporation of both objective and subjective knowledge in estimation. Also discussed is a technique, called heuristically constrained estimation (HCE) which is a particular interpretation of the Bayesian use of subjective priors. COSE, HCE, and classical maximum a posteriori probability (MAP) estimation are applied to a tracking problem
Keywords
Bayes methods; estimation theory; heuristic programming; knowledge representation; probability; tracking; Bayesian method; coordinated objective/subjective estimation; data association; estimation theory; heuristically constrained estimation; maximum a posteriori probability; probability models; subjective knowledge; tracking; Assembly; Bayesian methods; Constraint optimization; Estimation theory; Frequency; Fuzzy sets; Fuzzy systems; Image processing; Knowledge engineering; Probability; Signal processing;
fLanguage
English
Journal_Title
Aerospace and Electronic Systems, IEEE Transactions on
Publisher
ieee
ISSN
0018-9251
Type
jour
DOI
10.1109/7.220959
Filename
220959
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