Title :
A tight upper bound on the Bayesian probability of error
Author :
Hashlamoun, W.A. ; Varshney, P.K. ; Samarasooriya, V.N.S.
Author_Institution :
Dept. of Electr. Eng., Birzeit Univ., Israel
fDate :
2/1/1994 12:00:00 AM
Abstract :
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
Keywords :
Bayes methods; decision theory; pattern recognition; probability; Bayesian probability; minimum error probability; statistical pattern recognition; tight upper bound; Bayesian methods; Computer errors; Laboratories; Machine intelligence; Pattern recognition; Performance analysis; Probability; System performance; Testing; Upper bound;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
