The formulation of the decision making process of a failure detection algorithm as a Bayes sequential decision problem provides a simple conceptualization of the decision rule design problem. As the optimal Bayes rule is not computable, a methodology that is based on the Bayesian approach and aimed at a reduced computational requirement is developed for designing suboptimal rules. A numerical algorithm is constructed to facilitate the design and performance evaluation of these suboptimal rules. The result of applying this design methodology to an example shows that this approach is potentially a useful one.


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    Title :

    Bayesian design of decision rules for failure detection


    Contributors:


    Publication date :

    1984-11-01



    Type of media :

    Miscellaneous


    Type of material :

    No indication


    Language :

    English


    Keywords :