A Tight Upper Bound on the Bayesian Probability of Error

W. A. Hashlamoun; P. K. Varshney; V. N.S. Samarasooriya

doi:10.1109/34.273728

A Tight Upper Bound on the Bayesian Probability of Error

W. A. Hashlamoun, P. K. Varshney, V. N.S. Samarasooriya

Department of Electrical Engineering & Computer Science

Research output: Contribution to journal › Article › peer-review

26 Scopus citations

Abstract

In this paper, we present a new upper bound on the minimum probability of error of Bayesian decision systems. 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.

Original language	English (US)
Pages (from-to)	220-224
Number of pages	5
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	16
Issue number	2
DOIs	https://doi.org/10.1109/34.273728
State	Published - Feb 1994

Keywords

Ali-Silvey distance measures
Bayesian decision systems
divergence
minimum probability of error
probability of error bounds
statistical pattern recognition

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Computational Theory and Mathematics
Artificial Intelligence
Applied Mathematics

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10.1109/34.273728

Cite this

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title = "A Tight Upper Bound on the Bayesian Probability of Error",

abstract = "In this paper, we present a new upper bound on the minimum probability of error of Bayesian decision systems. 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 = "Ali-Silvey distance measures, Bayesian decision systems, divergence, minimum probability of error, probability of error bounds, statistical pattern recognition",

author = "Hashlamoun, {W. A.} and Varshney, {P. K.} and Samarasooriya, {V. N.S.}",

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KW - minimum probability of error

KW - probability of error bounds

KW - statistical pattern recognition

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A Tight Upper Bound on the Bayesian Probability of Error

Abstract

Keywords

ASJC Scopus subject areas

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