Quantization of prior probabilities for hypothesis testing

被引：28

作者：

Varshney, Kush R. ^{[1
]}

Varshney, Lav R. ^{[1
]}

机构：

[1] MIT, Informat & Decis Syst Lab, Cambridge, MA 02139 USA

来源：

IEEE TRANSACTIONS ON SIGNAL PROCESSING | 2008年 / 56卷 / 10期

基金：

美国国家科学基金会;

关键词：

Bayesian hypothesis testing; Bayes risk error; categorization; classification; detection; quantization;

D O I：

10.1109/TSP.2008.928164

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, Bayesian hypothesis testing is investigated when the prior probabilities of the hypotheses, taken as a random vector, are quantized. Nearest neighbor and centroid conditions are derived using mean Bayes risk error (NORE) as a distortion measure for quantization. A high-resolution approximation to the distortion-rate function is also obtained. Human decision making in segregated populations is studied assuming Bayesian hypothesis testing with quantized priors.

引用

页码：4553 / 4562

页数：10

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