DocumentCode
891344
Title
A stochastic multisample extension of Morris´s robust detector in bounded amplitude noise
Author
Jones, L.K.
Author_Institution
Dept. of Math., Lowell Univ., MA
Volume
34
Issue
5
fYear
1988
fDate
9/1/1988 12:00:00 AM
Firstpage
973
Lastpage
978
Abstract
A Bayesian approach to the problem of finite sample detection of a signal in an unknown noise environment is formulated. A mathematical solution is given for the minimax (robust) test for detecting the presence of a stochastic signal of known prior probability in unknown additive noise of bounded magnitude. This solution remains valid for a constant signal with identical components when the additive noises are independent. This extends results of J.M. Morris (ibid., vol.IT-62, p.199-209, March 1980). Worst-case performance bounds for detecting the presence of a pattern class are derived
Keywords
Bayes methods; signal detection; stochastic processes; Bayesian approach; Morris´s robust detector; bounded amplitude noise; constant signal; finite sample detection; stochastic multisample extension; unknown noise environment; Additive noise; Bayesian methods; Detectors; Minimax techniques; Noise robustness; Signal detection; Stochastic processes; Stochastic resonance; Testing; Working environment noise;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.21220
Filename
21220
Link To Document