On the stability of Bayes estimators for Gaussian processes
Abstract
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 QNlaws. 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.
 Publication:

NASA STI/Recon Technical Report N
 Pub Date:
 September 1982
 Bibcode:
 1982STIN...8319988M
 Keywords:

 Bayes Theorem;
 Estimating;
 Random Processes;
 Signal Processing;
 Hilbert Space;
 Kalman Filters;
 Probability Distribution Functions;
 Random Noise;
 RootMeanSquare Errors;
 Communications and Radar