Abstract
A Bayesian approach to the problem of finite sample detection of a signal in an unknown noise environment is formulated. A mathematical solution is given for the minimax (robust) test for detecting the presence of a stochastic signal of known prior probability in unknown additive noise of bounded magnitude. This solution remains valid for a constant signal with identical components when the additive noises are independent. This extends results of J.M. Morris (ibid., vol.IT-62, p.199-209, March 1980). Worst-case performance bounds for detecting the presence of a pattern class are derived.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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