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Robust detection of a weak signal with redescending M-estimators: A comparative study
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Shevlyakov, Georgy | - |
| dc.contributor.author | Lee, Jae Won | - |
| dc.contributor.author | Lee, Kyung Min | - |
| dc.contributor.author | Shin, Vladimir | - |
| dc.contributor.author | Kim, Kiseon | - |
| dc.date.available | 2020-04-24T13:25:48Z | - |
| dc.date.created | 2020-03-31 | - |
| dc.date.issued | 2010-01 | - |
| dc.identifier.issn | 0890-6327 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/2785 | - |
| dc.description.abstract | On finite samples redescending M-estimators outperform linear bounded Huber's M-estimators. To provide stable detection of a weak signal of arbitrary shape, robust Neyman-Pearson detection rules based on redescending M-estimators of location are introduced and Studied. It is shown that, on the whole, robust detectors based on redescending M-estimators Outperform conventional Huber's linear bounded detectors rules under light- and heavy-tailed noise distributions both on large and small samples. Copyright (C) 2009 John Wiley & Sons, Ltd. | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | WILEY | - |
| dc.subject | GAUSSIAN-NOISE | - |
| dc.subject | PROBABILITY | - |
| dc.subject | LOCATION | - |
| dc.title | Robust detection of a weak signal with redescending M-estimators: A comparative study | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Lee, Jae Won | - |
| dc.identifier.doi | 10.1002/acs.1104 | - |
| dc.identifier.scopusid | 2-s2.0-73849146139 | - |
| dc.identifier.wosid | 000273681900004 | - |
| dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, v.24, no.1, pp.33 - 40 | - |
| dc.citation.title | INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING | - |
| dc.citation.volume | 24 | - |
| dc.citation.number | 1 | - |
| dc.citation.startPage | 33 | - |
| dc.citation.endPage | 40 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Article | - |
| dc.description.journalClass | 1 | - |
| dc.subject.keywordPlus | GAUSSIAN-NOISE | - |
| dc.subject.keywordPlus | PROBABILITY | - |
| dc.subject.keywordPlus | LOCATION | - |
| dc.subject.keywordAuthor | robust detection | - |
| dc.subject.keywordAuthor | redescending M-estimators | - |
| dc.subject.keywordAuthor | weak signals | - |
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Related Researcher
- LEE, JAE WON
- College of Engineering (Department of Mathematics and Big Data Science)