DocumentCode
1112432
Title
A class of memoryless robust detectors in dependent noise
Author
Cheung, Julian ; Kurz, Ludwik
Author_Institution
Dept. of Electr. Eng., New York Inst. of Technol., NY, USA
Volume
42
Issue
5
fYear
1994
fDate
5/1/1994 12:00:00 AM
Firstpage
1272
Lastpage
1275
Abstract
A new general approach to the formulation of a detector in non-Gaussian noise satisfying the strong mixing condition is introduced. The only statistical knowledge required for the optimal design is a set of parameters which can be estimated from data and recursively updated. This eliminates the requirement that exact distributions be known and leads naturally to efficient adaptive detectors
Keywords
noise; signal detection; adaptive detectors; dependent noise; memoryless robust detectors; nonGaussian noise; parameter estimation; signal detection; statistical knowledge; strong mixing condition; Additive noise; Detectors; Niobium; Noise robustness; Probability; Random variables; Recursive estimation; Signal processing; Space stations; Statistical analysis;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.295184
Filename
295184
Link To Document