Further discussions on adaptive filters to improve the wavelet shrinkage method

Teng-Chieh Yang, Y. Chiang, F. Chang
{"title":"Further discussions on adaptive filters to improve the wavelet shrinkage method","authors":"Teng-Chieh Yang, Y. Chiang, F. Chang","doi":"10.1109/ICSSE.2016.7551646","DOIUrl":null,"url":null,"abstract":"We earlier proposed a novel on-line denoising structure which utilized the adaptive filter to improve the wavelet shrinkage and did acquire some positive results. In this paper, we will have a further discussion based on this structure. Topics include parameter adjustments, LMS non-causal cases, the decision of both DWT level and mother wavelet, and RLS algorithm. Based on these discussions, we will be able to fine tune our denoising structure and come up with better results.","PeriodicalId":175283,"journal":{"name":"2016 International Conference on System Science and Engineering (ICSSE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE.2016.7551646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

We earlier proposed a novel on-line denoising structure which utilized the adaptive filter to improve the wavelet shrinkage and did acquire some positive results. In this paper, we will have a further discussion based on this structure. Topics include parameter adjustments, LMS non-causal cases, the decision of both DWT level and mother wavelet, and RLS algorithm. Based on these discussions, we will be able to fine tune our denoising structure and come up with better results.
进一步讨论了自适应滤波器对小波收缩方法的改进
我们之前提出了一种新的在线去噪结构,利用自适应滤波器来改善小波收缩,并取得了一些积极的结果。在本文中,我们将基于这种结构进行进一步的讨论。主题包括参数调整,LMS非因果情况,DWT水平和母小波的决定,以及RLS算法。基于这些讨论,我们将能够微调我们的去噪结构,并提出更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信