On the Stability of Bayes Estimators for Gaussian Processes
研究了高斯信号在加性高斯噪声下，当信号或噪声受污染时，贝叶斯估计量的均方误差上界，发现小污染下其性能接近最优。
We consider the Bayes estimator $\delta_0$ for a Gaussian signal process observed in the presence of additive Gaussian noise under contamination of the signal or noise by QN-laws, introduced by Gualtierotti (1979). Upper bounds on the increase in the mean square error of $\delta_0$ over the minimum possible mean square error under contaminated noise or contaminated signal are given. It is shown that the performance of $\delta_0$ is relatively close to optimal for small amounts of contamination.