{"title":"基于PSR-fastICA的谱致极化降噪方法","authors":"Wei Cen, Zhihua Li","doi":"10.1117/12.2685458","DOIUrl":null,"url":null,"abstract":"Spectrum-induced polarization (SIP) is a widely used geophysical exploration approach, but it is prone to noise. To address this issue, this paper proposes a noise reduction method that combines phase space reconstruction (PSR) and fast independent component analysis (fastICA). The proposed approach enhances the signal-to-noise ratio of SIP data by effectively removing noise. Experimental results show that the PSR-fastICA method significantly reduces noise in SIP signals.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A noise reduction method based on PSR-fastICA for spectrum-induced polarization data\",\"authors\":\"Wei Cen, Zhihua Li\",\"doi\":\"10.1117/12.2685458\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Spectrum-induced polarization (SIP) is a widely used geophysical exploration approach, but it is prone to noise. To address this issue, this paper proposes a noise reduction method that combines phase space reconstruction (PSR) and fast independent component analysis (fastICA). The proposed approach enhances the signal-to-noise ratio of SIP data by effectively removing noise. Experimental results show that the PSR-fastICA method significantly reduces noise in SIP signals.\",\"PeriodicalId\":305812,\"journal\":{\"name\":\"International Conference on Electronic Information Technology\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Electronic Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2685458\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Electronic Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2685458","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A noise reduction method based on PSR-fastICA for spectrum-induced polarization data
Spectrum-induced polarization (SIP) is a widely used geophysical exploration approach, but it is prone to noise. To address this issue, this paper proposes a noise reduction method that combines phase space reconstruction (PSR) and fast independent component analysis (fastICA). The proposed approach enhances the signal-to-noise ratio of SIP data by effectively removing noise. Experimental results show that the PSR-fastICA method significantly reduces noise in SIP signals.