A suboptimal estimation algorithm based on smoothing B splines

Smoothing cubic normalized B splines are used in synthesizing a suboptimal algorithm for estimation on Bayes criteria, maximum likelihood, and a posteriori density without constraint on the gaussian behavior of the corresponding distribution densities. The potential accuracy of the algorithm is eval...

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Bibliographic Details
Published inMeasurement techniques Vol. 49; no. 10; pp. 970 - 975
Main Authors Bezuglov, D. A., Sklyarov, A. V., Zabrodin, R. A., Reshetnikova, I. V.
Format Journal Article
LanguageEnglish
Published New York Springer Nature B.V 01.10.2006
Subjects
Algorithms
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Summary:Smoothing cubic normalized B splines are used in synthesizing a suboptimal algorithm for estimation on Bayes criteria, maximum likelihood, and a posteriori density without constraint on the gaussian behavior of the corresponding distribution densities. The potential accuracy of the algorithm is evaluated in accordance with the Cramer-Rao inequality.[PUBLICATION ABSTRACT]
ISSN:0543-1972
1573-8906
DOI:10.1007/s11018-006-0221-6