小波级数变换的计算方法

Yu Yue, Zhou Jian, Wang Yiliang, L. Fengting, Ge Chenghui
{"title":"小波级数变换的计算方法","authors":"Yu Yue, Zhou Jian, Wang Yiliang, L. Fengting, Ge Chenghui","doi":"10.1109/ICOSP.1998.770214","DOIUrl":null,"url":null,"abstract":"Because the discrete wavelet transform (DWT) can be computed effectively with a fast algorithm, the DWT is often used to approximate the continuous wavelet transform (CWT) and wavelet series transform (WST). Approximation accuracy is considered as an open problem in wavelet theory. In this paper, we firstly give three parts that affect the approximation accuracy. Based on sampling theory for wavelet subspaces, two kinds of prefilters are given; one can exactly compute the WST for any signal in this wavelet subspace and the other one can effectively approximate the true WST. Finally, numerical examples are given to show that our algorithms are effective.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"On the computation of wavelet series transform\",\"authors\":\"Yu Yue, Zhou Jian, Wang Yiliang, L. Fengting, Ge Chenghui\",\"doi\":\"10.1109/ICOSP.1998.770214\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Because the discrete wavelet transform (DWT) can be computed effectively with a fast algorithm, the DWT is often used to approximate the continuous wavelet transform (CWT) and wavelet series transform (WST). Approximation accuracy is considered as an open problem in wavelet theory. In this paper, we firstly give three parts that affect the approximation accuracy. Based on sampling theory for wavelet subspaces, two kinds of prefilters are given; one can exactly compute the WST for any signal in this wavelet subspace and the other one can effectively approximate the true WST. Finally, numerical examples are given to show that our algorithms are effective.\",\"PeriodicalId\":145700,\"journal\":{\"name\":\"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSP.1998.770214\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.1998.770214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

由于离散小波变换(DWT)可以用一种快速有效的算法进行计算,因此DWT常被用来近似连续小波变换(CWT)和小波序列变换(WST)。逼近精度是小波理论中的一个开放性问题。本文首先给出了影响近似精度的三个部分。基于小波子空间的采样理论,给出了两种预滤波器;一种方法可以精确地计算出小波子空间中任意信号的WST,另一种方法可以有效地逼近真实的WST。最后给出了数值算例,证明了算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
On the computation of wavelet series transform
Because the discrete wavelet transform (DWT) can be computed effectively with a fast algorithm, the DWT is often used to approximate the continuous wavelet transform (CWT) and wavelet series transform (WST). Approximation accuracy is considered as an open problem in wavelet theory. In this paper, we firstly give three parts that affect the approximation accuracy. Based on sampling theory for wavelet subspaces, two kinds of prefilters are given; one can exactly compute the WST for any signal in this wavelet subspace and the other one can effectively approximate the true WST. Finally, numerical examples are given to show that our algorithms are effective.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A new estimation formula for minimum filter length of optimum FIR digital filters A fuzzy associative memory pattern classifier Randomized method for planar motion estimation and matching points A robust speech feature-perceptive scalogram based on wavelet analysis A new class of feature-orientated motion estimation for motion pictures
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1