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CORR
2008
Springer

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Quantization of Prior Probabilities for Hypothesis Testing

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Quantization of Prior Probabilities for Hypothesis Testing

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Abstract--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 (MBRE) 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.

Kush R. Varshney, Lav R. Varshney

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Added	09 Dec 2010
Updated	09 Dec 2010
Type	Journal
Year	2008
Where	CORR
Authors	Kush R. Varshney, Lav R. Varshney

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