Error probability in dependent pattern classification (Corresp.)
John Forsyth · IEEE Transactions on Information Theory · 1972
This correspondence derives an upper bound on the probability of error of them-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.