An approximate representation of heavy-tailed noise: Bi-parameter Cauchy-Gaussian mixture model

Xutao Li, Zetao Chen, Shouyong Wang
{"title":"An approximate representation of heavy-tailed noise: Bi-parameter Cauchy-Gaussian mixture model","authors":"Xutao Li, Zetao Chen, Shouyong Wang","doi":"10.1109/ICOSP.2008.4697072","DOIUrl":null,"url":null,"abstract":"As a non-Gaussian statistic model, alpha stable distribution has gained much attention due to its generality to represent heavy-tailed and impulsive interference. Unfortunately, there is no closed form expression for the probability density function of alpha-stable distributions. Hereby, finding the approximate expressions is of importance for signal detection and denoising. In this paper, we present a novel approximate expression, which is a simplified version of Cauchy-Gaussian mixture (CGM) for symmetric alpha-stable (SalphaS) distribution, called Bi-parameter CGM (BCGM). Such a model has a complete closed-form expression, and hence is more tractable than classical GMM and CGM.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 9th International Conference on Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.2008.4697072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

As a non-Gaussian statistic model, alpha stable distribution has gained much attention due to its generality to represent heavy-tailed and impulsive interference. Unfortunately, there is no closed form expression for the probability density function of alpha-stable distributions. Hereby, finding the approximate expressions is of importance for signal detection and denoising. In this paper, we present a novel approximate expression, which is a simplified version of Cauchy-Gaussian mixture (CGM) for symmetric alpha-stable (SalphaS) distribution, called Bi-parameter CGM (BCGM). Such a model has a complete closed-form expression, and hence is more tractable than classical GMM and CGM.
重尾噪声的近似表示:双参数柯西-高斯混合模型
α稳定分布作为一种非高斯统计模型,由于其表现重尾和脉冲干扰的普遍性而受到广泛关注。不幸的是,对于稳定分布的概率密度函数没有封闭形式的表达式。因此,寻找近似表达式对于信号检测和去噪具有重要意义。本文提出了一种新的近似表达式,它是对称α -稳定分布(SalphaS)的Cauchy-Gaussian mixture (CGM)的简化版本,称为双参数CGM (BCGM)。该模型具有完备的封闭表达式,比经典的GMM和CGM更易于处理。
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