{"title":"Quadratic Form Innovation to Blind Source Separation","authors":"Zhenwei Shi, Zhanxing Zhu, X. Tan, Zhi-guo Jiang","doi":"10.1109/ICNC.2009.328","DOIUrl":null,"url":null,"abstract":"This paper proposes a blind source separation (BSS) method based on the quadratic form innovation of original sources, which includes linear predictability and energy (square) predictability as special cases. A simple algorithm is presented by minimizing a loss function of the quadratic form innovation. Simulations by source signals with linear or square temporal autocorrelations verify the efficient implementation of the proposed method.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"12 31","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fifth International Conference on Natural Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2009.328","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
This paper proposes a blind source separation (BSS) method based on the quadratic form innovation of original sources, which includes linear predictability and energy (square) predictability as special cases. A simple algorithm is presented by minimizing a loss function of the quadratic form innovation. Simulations by source signals with linear or square temporal autocorrelations verify the efficient implementation of the proposed method.