Small-sample estimation of the error of the optimal binary filter

Abstract

Precise small-sample estimation of the error of an optimal filter is theoretically limited. This paper shows the possibility of obtaining better estimation in a Bayesian context by postulating prior knowledge regarding the probability distribution of the model. Prior knowledge is employed to estimate the estimation error, and thereby obtain a better… (More)

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