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Let F be the fault of a system which takes value in Ω={fi}, and pi be the known probability of occurrence of fi. Let T={tj} be a sufficient set of tests available for diagnosing the system, and cj be the cost of tj. The number of possible responses for each test in T may be different. The author introduces the cost-entropy function as an information-theoretic lower bound on Cmin the expected cost of an optimal testing tree. The author also obtains a universal upper bound of Cmin when {pi} is unknown, and a refined upper bound on Cmin when {pi} is known. The author's results are essential for developing heuristic strategies to search for optimal and suboptimal testing trees
Published in:
Systems, Man and Cybernetics, IEEE Transactions on
(Volume:24
,
Issue:
7
)
Date of Publication: Jul 1994
- Page(s):
- 1074 - 1082
- ISSN :
- 0018-9472
- INSPEC Accession Number:
- 4742117
- Digital Object Identifier :
- 10.1109/21.297798
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Jul 1994
- Sponsored by :
- IEEE Systems, Man, and Cybernetics Society
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