{"title":"基于稳定动态模型反演的非最小相位系统独立分量分析","authors":"Shuichi Fukunaga, Kenji Fujimoto","doi":"10.23919/ECC.2007.7068597","DOIUrl":null,"url":null,"abstract":"This paper proposes an independent component analysis method using stable dynamic model inversion for nonminimum phase systems. First, a stable inverse filter is constructed based on a Kalman filter in order to estimate the input sequence of the given plant. Second, the learning algorithm is derived by minimizing the Kullback-Leibler divergence. Furthermore, a numerical simulation demonstrates the effectiveness of the proposed method.","PeriodicalId":407048,"journal":{"name":"2007 European Control Conference (ECC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Independent component analysis for nonminimum phase systems using stable dynamic model inversion\",\"authors\":\"Shuichi Fukunaga, Kenji Fujimoto\",\"doi\":\"10.23919/ECC.2007.7068597\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an independent component analysis method using stable dynamic model inversion for nonminimum phase systems. First, a stable inverse filter is constructed based on a Kalman filter in order to estimate the input sequence of the given plant. Second, the learning algorithm is derived by minimizing the Kullback-Leibler divergence. Furthermore, a numerical simulation demonstrates the effectiveness of the proposed method.\",\"PeriodicalId\":407048,\"journal\":{\"name\":\"2007 European Control Conference (ECC)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 European Control Conference (ECC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ECC.2007.7068597\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 European Control Conference (ECC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ECC.2007.7068597","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Independent component analysis for nonminimum phase systems using stable dynamic model inversion
This paper proposes an independent component analysis method using stable dynamic model inversion for nonminimum phase systems. First, a stable inverse filter is constructed based on a Kalman filter in order to estimate the input sequence of the given plant. Second, the learning algorithm is derived by minimizing the Kullback-Leibler divergence. Furthermore, a numerical simulation demonstrates the effectiveness of the proposed method.