DocumentCode
3394309
Title
Reasoning from uncertain data: a bit enhancement
Author
Cooper, Laurence J. ; Smith, Dennis E.
Author_Institution
SIGMAX, New Freedom, PA, USA
fYear
1989
fDate
25-28 Sep 1989
Firstpage
146
Lastpage
149
Abstract
It is proposed that artificial intelligence (AI) principles, coupled with powerful Bayesian statistical inference techniques, can be successfully applied to built-in-test (BIT) technology and can significantly contribute to the improvement of avionics BIT diagnostic capabilities. The goal is to extract more information from available data provided by the BIT, rather than to expand its testing capabilities. The proposed approach is illustrated by a TACAN (tactical air navigation) example
Keywords
Bayes methods; aircraft instrumentation; artificial intelligence; automatic testing; electronic equipment testing; inference mechanisms; military systems; probability; statistical analysis; Bayesian statistical inference; TACAN; automatic testing; avionics; bit; built-in-test; tactical air navigation; Aerospace electronics; Artificial intelligence; Bayesian methods; Built-in self-test; Data mining; Information analysis; Isolation technology; Logic; Testing; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
AUTOTESTCON '89. IEEE Automatic Testing Conference. The Systems Readiness Technology Conference. Automatic Testing in the Next Decade and the 21st Century. Conference Record.
Conference_Location
Philadelphia, PA
Type
conf
DOI
10.1109/AUTEST.1989.81112
Filename
81112
Link To Document