Importance sampling is a technique which can significantly reduce the number of Monte Carlos necessary to accurately estimate the probability of low-probability of occurrence events (e.g., the probability of false alarm P/sub F/ associated with a given detection scheme). A new technique called the Chernoff Importance Sampling Method is introduced. It is shown that the number of required Monte Carlos can be reduced by a factor of a Chernoff-like bound on P/sub F/. In addition, techniques for choosing the multiplying factor of the distorted variance method (the most common method used in importance sampling) are presented.


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    Title :

    New results in importance sampling [of false alarm statistics]


    Contributors:
    Gerlach, K. (author)


    Publication date :

    1999-07-01


    Size :

    387226 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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