DocumentCode :
3281304
Title :
Improving Nonparametric Detectors via Stochastic Resonance
Author :
Chen, Hao ; Varshney, Pramod K. ; Kay, Steven ; Michels, James H.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., NY
fYear :
2006
fDate :
22-24 March 2006
Firstpage :
56
Lastpage :
61
Abstract :
This paper investigates the problem of stochastic resonance in some non-parametric detection schemes such as the sign detector, Wilcoxon detector and dead-zone limiter detector. Detection performance comparisons are made between the original detectors and noise modified detectors. Potential improvement of detection performance via stochastic resonance (SR) for each detection scheme is determined. The optimal SR noise for the sign detector is derived. Asymptotic detection performance is evaluated for the three detectors. For the finite sample size problem, we demonstrate improvability via some detection examples where the detection performance of these detectors can be improved when suitable noise is added.
Keywords :
nonparametric statistics; signal detection; stochastic processes; SR; asymptotic detection performance; noise modified detectors; nonparametric detectors; stochastic resonance; Background noise; Detectors; Gaussian noise; Noise robustness; Nonlinear systems; Signal detection; Signal to noise ratio; Stochastic resonance; Strontium; System testing; Hypothesis Testing; Non-parametric Detection; Stochastic Resonance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Sciences and Systems, 2006 40th Annual Conference on
Conference_Location :
Princeton, NJ
Print_ISBN :
1-4244-0349-9
Electronic_ISBN :
1-4244-0350-2
Type :
conf
DOI :
10.1109/CISS.2006.286430
Filename :
4067776
Link To Document :
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