Methods of Signal Processing

Hypothesis Testing with Incompletely Known Distribution Function of the Observations and Unknown A Priori Probabilities of the Hypotheses

A. A. Slepokurov


Abstract: An optimal decision rule is derived for testing two hypotheses under incompletely known distributions of the observed signals and unknown a priori probabilities of the hypotheses. Optimality is understood in the sense of minimizing the maximum excess of average risk over Bayesian risk. Some examples are considered.

UDC: 621.391.1:519.27

Received: 29.07.1988
Revised: 23.07.1990

 English version: Problems of Information Transmission, 1991, 27:1, 58–66

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