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- W1977165177 abstract "A randomized decision rule is derived and proved to be the saddlepoint solution of the robust detection problem for known signals in independent, unknown-mean, amplitude-bounded noise. The saddlepoint solution ϕ0 uses an equally-likely, mixed strategy to choose one of N Bayesian, single-threshold decision rules ϕi 0, i = 1,...., N obtained previously by Morris [4]. These decision rules are also all optimal against the maximin (least favorable), nonrandomized, noise probability density f0, where f0 is a picket-fence function with N pickets on its domain. The pair (ϕ0, f0) are shown to satisfy the saddlepoint condition for probability of error, i.e., Pe(ϕ0, f) ≤ Pe(ϕ0, f0) ϕ Pe(ϕ, f0), Vf, Vϕ for this problem. The decision rule ϕ0 is shown also to be an equalizer rule, i.e., Pe(ϕ0, f)= Pe(ϕ0, f0), Vf, with 4-1 #x02264; Pe(ϕ0, f0) = 2-1 (1-N-1) ≤ 2-1, N ≥ 2. We conclude that nature can force the communicator to use an optimal randomized decision rule that generates large probability of error and does not improve when less pernicious conditions prevail." @default.
- W1977165177 created "2016-06-24" @default.
- W1977165177 creator A5019742991 @default.
- W1977165177 date "1979-12-01" @default.
- W1977165177 modified "2023-10-16" @default.
- W1977165177 title "Some results on robust detection for known signals and additive unknown-mean amplitude-bounded noise" @default.
- W1977165177 doi "https://doi.org/10.1109/cdc.1979.270222" @default.
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