DocumentCode :
917208
Title :
Nonparametric detectors based on m-interval partitioning
Author :
Ching, Yau Chau ; Kurz, Ludwik
Volume :
18
Issue :
2
fYear :
1972
fDate :
3/1/1972 12:00:00 AM
Firstpage :
251
Lastpage :
257
Abstract :
A new class of nonparametric detectors based on 
- interval partitioning is introduced. It is easier to treat analytically and implement practically than the widely used class of nonparametric detectors based on rank partitioning of the received signal space. In addition, these new detectors are robust or relatively insensitive to the underlying noise distribution. If the quantiles of the noise distribution are known exactly, the structure of the detector is particularly simple. Some general results for an adaptive system, when the quantiles of the noise distribution must be estimated, were also obtained.
- interval partitioning is introduced. It is easier to treat analytically and implement practically than the widely used class of nonparametric detectors based on rank partitioning of the received signal space. In addition, these new detectors are robust or relatively insensitive to the underlying noise distribution. If the quantiles of the noise distribution are known exactly, the structure of the detector is particularly simple. Some general results for an adaptive system, when the quantiles of the noise distribution must be estimated, were also obtained.Keywords :
Nonparametric detection; Adaptive systems; Detectors; Gaussian noise; Noise robustness; Signal analysis; Signal detection; Statistical analysis; Statistical distributions; Testing; Working environment noise;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1972.1054788
Filename :
1054788
Link To Document :
