ESE 471 Two formulas for the Bayes Threshold in Gaussian Noise
Автор: Neal Patwari
Загружено: 2021-02-21
Просмотров: 1074
Following up on my previous segment on the general formula for the minimum probability of error detector for arbitrary conditional distributions given H0 and given H1, in this segment I find the threshold when the noise is additive Gaussian. There are two expressions, the first a general expression when P[H0] and P[H1] are different, and another for when they're identical. In the identical symbol probabilities case, the threshold is shown to be halfway in between the two symbols. In the general case, the symbol that is more likely "pushes" the threshold away from its symbol.
For all of my 471 course materials, check out https://span.engineering.wustl.edu/es....
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