Issue No. 01 - January (1996 vol. 18)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.476017
<p><b>Abstract</b>—This paper presents new upper and lower bounds on the minimum probability of error of Bayesian decision systems for the two-class problem. These bounds can be made arbitrarily close to the exact minimum probability of error, making them tighter than any previously known bounds.</p>
Bayesian decision, probability of error, statistical pattern recognition.
H. Avi-Itzhak and T. Diep, "Arbitrarily Tight Upper and Lower Bounds on the Bayesian Probability of Error," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 18, no. , pp. 89-91, 1996.