{"title":"引入模糊理论的独立分量分析的基本尝试","authors":"N. Kakasaki, K. Tsuruta, A. Ikuta, M. Ohta","doi":"10.1109/ROMAN.2000.892466","DOIUrl":null,"url":null,"abstract":"The problem of independent component analysis and/or blind signal separation becomes a very popular and emerging field of research, because the problem contains many potential applications. In such a problem, a priori information we can utilize is the statistical independency between source signals. In many actual fields, the independent component analysis must play an essential role but it also contains problems: it cannot be applicable to non-physical quantity like a human psychological or sensory one, etc. This paper proposes a fundamental trial of independent component analysis by introducing the fuzzy theory. More precisely, the parameters of unknown system are estimated on the basis of fuzzy observations. Finally, the effectiveness of this method is confirmed through digital simulation.","PeriodicalId":337709,"journal":{"name":"Proceedings 9th IEEE International Workshop on Robot and Human Interactive Communication. IEEE RO-MAN 2000 (Cat. No.00TH8499)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A fundamental trial on independent component analysis under the introduction of fuzzy theory\",\"authors\":\"N. Kakasaki, K. Tsuruta, A. Ikuta, M. Ohta\",\"doi\":\"10.1109/ROMAN.2000.892466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of independent component analysis and/or blind signal separation becomes a very popular and emerging field of research, because the problem contains many potential applications. In such a problem, a priori information we can utilize is the statistical independency between source signals. In many actual fields, the independent component analysis must play an essential role but it also contains problems: it cannot be applicable to non-physical quantity like a human psychological or sensory one, etc. This paper proposes a fundamental trial of independent component analysis by introducing the fuzzy theory. More precisely, the parameters of unknown system are estimated on the basis of fuzzy observations. Finally, the effectiveness of this method is confirmed through digital simulation.\",\"PeriodicalId\":337709,\"journal\":{\"name\":\"Proceedings 9th IEEE International Workshop on Robot and Human Interactive Communication. IEEE RO-MAN 2000 (Cat. No.00TH8499)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 9th IEEE International Workshop on Robot and Human Interactive Communication. IEEE RO-MAN 2000 (Cat. No.00TH8499)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROMAN.2000.892466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 9th IEEE International Workshop on Robot and Human Interactive Communication. IEEE RO-MAN 2000 (Cat. No.00TH8499)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROMAN.2000.892466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fundamental trial on independent component analysis under the introduction of fuzzy theory
The problem of independent component analysis and/or blind signal separation becomes a very popular and emerging field of research, because the problem contains many potential applications. In such a problem, a priori information we can utilize is the statistical independency between source signals. In many actual fields, the independent component analysis must play an essential role but it also contains problems: it cannot be applicable to non-physical quantity like a human psychological or sensory one, etc. This paper proposes a fundamental trial of independent component analysis by introducing the fuzzy theory. More precisely, the parameters of unknown system are estimated on the basis of fuzzy observations. Finally, the effectiveness of this method is confirmed through digital simulation.