Error Exponents for Hypothesis Testing of the General Source
Luc Devroye, László Györfi, Gábor Lugosi
Abstract
Luc Devroye, László Györfi, Gábor Lugosi
Abstract
In this correspondence, we consider the simple hypothesis testing problems for general sources in the sence of Han and Verdu. Re- cently Han established a compact formula for the supremum of achievable exponents for the second-kind of error probability under the asymptotic constraint of the form on the first-kind of error probability , where is a given positive number. We investigate the same hypothesis testing problems studied by Han. The aim of the correspondence is to give a new expression for the supremum of achievable error exponents. Our formula is expressed in terms of the divergences and given in quite different forms from Han's expression.
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In this correspondence, we consider the simple hypothesis testing problems for general sources in the sence of Han and Verdu. Re- cently Han established a compact formula for the supremum of achievable exponents for the second-kind of error probability under the asymptotic constraint of the form on the first-kind of error probability , where is a given positive number. We investigate the same hypothesis testing problems studied by Han. The aim of the correspondence is to give a new expression for the supremum of achievable error exponents. Our formula is expressed in terms of the divergences and given in quite different forms from Han's expression.
Key concepts: Infimum and supremum, Mathematics, Constraint (computer-aided design), Simple (philosophy), Statistical hypothesis testing, Expression (computer science), Applied mathematics, Discrete mathematics