Abstract
Change detection algorithms are proposed that are based on the comparison of distribution functions. Estimated values of distributions are associated with a binomial distribution that is used to define fuzzy similarity classes. Fuzzy concepts are used to combine partial evaluations to a measure that indicates the departure of a signal from its reference.
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