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Error probability in dependent pattern classification (Corresp.)

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1 Author(s)

This correspondence derives an upper bound on the probability of error of the m -class Bayes decision process when the patterns observed have first-order stochastic dependence. The bound is derived by applying an information-theoretic approach in which both the equivocation and the Bhattacharyya coefficient play a role.

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Information Theory, IEEE Transactions on  (Volume:18 ,  Issue: 5 )