Arbitrarily tight upper and lower bounds on the Bayesianprobability of error
Avi-Itzhak, H.
Thanh Diep
Canon Res. Center America, Palo Alto, CA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Jan 1996
Volume: 18,
Issue: 1
On page(s): 89-91
ISSN: 0162-8828
References Cited: 5
CODEN: ITPIDJ
INSPEC Accession Number: 5179886
Digital Object Identifier: 10.1109/34.476017
Current Version Published: 2002-08-06
Abstract
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
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
