Improving nonparametric detectors via stochastic resonance

Chen Hao, Pramod K. Varshney, Steven Kay, James H. Michels

Research output: Chapter in Book/Entry/PoemConference contribution

4 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2006 IEEE Conference on Information Sciences and Systems, CISS 2006 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages56-61
Number of pages6
ISBN (Print)1424403502, 9781424403509
DOIs
StatePublished - 2006
Event2006 40th Annual Conference on Information Sciences and Systems, CISS 2006 - Princeton, NJ, United States
Duration: Mar 22 2006Mar 24 2006

Publication series

Name2006 IEEE Conference on Information Sciences and Systems, CISS 2006 - Proceedings

Other

Other2006 40th Annual Conference on Information Sciences and Systems, CISS 2006
Country/TerritoryUnited States
CityPrinceton, NJ
Period3/22/063/24/06

Keywords

  • Hypothesis testing
  • Nonparametric detection
  • Stochastic resonance

ASJC Scopus subject areas

  • General Computer Science

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