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Issue No.02 - February (1994 vol.16)
pp: 220-224
ABSTRACT
<p>In this paper, we present a new upper bound on the minimum probability of error of Bayesian decision systems for statistical pattern recognition. This new bound is continuous everywhere and is shown to be tighter than several existing bounds such as the Bhattacharyya and the Bayesian bounds. Numerical results are also presented.</p>
INDEX TERMS
pattern recognition; Bayes methods; probability; decision theory; statistical pattern recognition; tight upper bound; Bayesian probability; minimum error probability
CITATION
W.A. Hashlamoun, P.K. Varshney, V.N.S. Samarasooriya, "A Tight Upper Bound on the Bayesian Probability of Error", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.16, no. 2, pp. 220-224, February 1994, doi:10.1109/34.273728
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