Step-down approach for wavelet thresholding
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lim, M | - |
dc.contributor.author | Mun, BM | - |
dc.contributor.author | Bae, Suk Joo | - |
dc.date.accessioned | 2022-07-09T11:54:03Z | - |
dc.date.available | 2022-07-09T11:54:03Z | - |
dc.date.created | 2021-05-11 | - |
dc.date.issued | 2019-08 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/147396 | - |
dc.description.abstract | Wavelet thresholding is one of the effective denoising methods for signal processing. It eliminates the noises by removing wavelet coefficients less than the specified threshold. The existing methods set their threshold values based on the variance or length of the signal. However, these approaches are not able to consider the overall trend or the characteristics of data effectively. In this paper, we proposed the step-down denoising for wavelet thresholding. The step-down approach is a data reduction method that defines the threshold value by calculating the order statistics of wavelet coefficients. The suggested method is applied to four types of sample data with various levels of signal-to-noise ratio (SNR). To evaluate the performance of this approach, the comparison of the denoising results in terms of plotting and average root mean square error (AMSE) is carried out. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | International Society of Science and Applied Technologies | - |
dc.title | Step-down approach for wavelet thresholding | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Bae, Suk Joo | - |
dc.identifier.scopusid | 2-s2.0-85072286532 | - |
dc.identifier.bibliographicCitation | Proceedings - 25th ISSAT International Conference on Reliability and Quality in Design, pp.220 - 222 | - |
dc.relation.isPartOf | Proceedings - 25th ISSAT International Conference on Reliability and Quality in Design | - |
dc.citation.title | Proceedings - 25th ISSAT International Conference on Reliability and Quality in Design | - |
dc.citation.startPage | 220 | - |
dc.citation.endPage | 222 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Discrete wavelet transforms | - |
dc.subject.keywordPlus | Mean square error | - |
dc.subject.keywordPlus | Signal processing | - |
dc.subject.keywordPlus | Denoising methods | - |
dc.subject.keywordPlus | Order statistics | - |
dc.subject.keywordPlus | Reduction method | - |
dc.subject.keywordPlus | Root mean square errors | - |
dc.subject.keywordPlus | Step down procedures | - |
dc.subject.keywordPlus | Wavelet coefficients | - |
dc.subject.keywordPlus | Wavelet shrinkage | - |
dc.subject.keywordPlus | Wavelet thresholding | - |
dc.subject.keywordPlus | Signal to noise ratio | - |
dc.subject.keywordAuthor | Discrete Wavelet Transform | - |
dc.subject.keywordAuthor | Signal Processing | - |
dc.subject.keywordAuthor | Step-Down Procedure | - |
dc.subject.keywordAuthor | Wavelet Shrinkage | - |
dc.subject.keywordAuthor | Wavelet Thresholding | - |
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