{"title":"基于矩匹配的盲源分离","authors":"F. Ghassemi, H. Amindavar","doi":"10.1109/ISSPA.2005.1580973","DOIUrl":null,"url":null,"abstract":"The Blind Source Separation (BSS) is a fundamental and challenging problem in signal processing. A new method based on the fractional moments and simulated annealing is presented in this paper. Fractional moments are used as a new measure of separation criterion contrary to the traditional integer moments. This is inspired by the fact that fractional moments lead to an enhanced estimation of the probability density function (PDF). Simulated Annealing (SA) is selected as the optimization algorithm to avoid being trapped into local minima. Simulation results validate the applicability of the new strategy for BSS .","PeriodicalId":385337,"journal":{"name":"Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Blind source separation based on moments matching\",\"authors\":\"F. Ghassemi, H. Amindavar\",\"doi\":\"10.1109/ISSPA.2005.1580973\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Blind Source Separation (BSS) is a fundamental and challenging problem in signal processing. A new method based on the fractional moments and simulated annealing is presented in this paper. Fractional moments are used as a new measure of separation criterion contrary to the traditional integer moments. This is inspired by the fact that fractional moments lead to an enhanced estimation of the probability density function (PDF). Simulated Annealing (SA) is selected as the optimization algorithm to avoid being trapped into local minima. Simulation results validate the applicability of the new strategy for BSS .\",\"PeriodicalId\":385337,\"journal\":{\"name\":\"Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005.\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPA.2005.1580973\",\"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 of the Eighth International Symposium on Signal Processing and Its Applications, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPA.2005.1580973","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Blind Source Separation (BSS) is a fundamental and challenging problem in signal processing. A new method based on the fractional moments and simulated annealing is presented in this paper. Fractional moments are used as a new measure of separation criterion contrary to the traditional integer moments. This is inspired by the fact that fractional moments lead to an enhanced estimation of the probability density function (PDF). Simulated Annealing (SA) is selected as the optimization algorithm to avoid being trapped into local minima. Simulation results validate the applicability of the new strategy for BSS .