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 QN-laws. 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. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1982
Accession Number
ADA121471

Entities

People

  • Ian W. Mckeague

Organizations

  • Florida State University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Banach Space
  • Data Science
  • Differential Equations
  • Estimators
  • Gaussian Distributions
  • Gaussian Noise
  • Gaussian Processes
  • Hilbert Space
  • Information Science
  • Information Theory
  • Mathematical Filters
  • Probability
  • Random Variables
  • Signal Processing
  • Statistical Algorithms
  • Statistics
  • Stochastic Processes

Fields of Study

  • Engineering

Readers

  • Statistical inference.