{"title":"基于支持向量机分类器的数字调制识别","authors":"Hussam Mustafa, Miloš Doroslova","doi":"10.1109/ACSSC.2004.1399565","DOIUrl":null,"url":null,"abstract":"We propose four features to classify amplitude shift keying with two levels and four levels, binary phase shift keying, quadrature phase keying, frequency shift keying with two carriers and four carriers. After that we present a new method of classification based on support vector machine (SVM) that uses the four proposed features. We study the performance of SVM classifier and compare it to the previous work done in the literature on the digital modulation classification problem.","PeriodicalId":396779,"journal":{"name":"Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004.","volume":"151 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":"{\"title\":\"Digital modulation recognition using support vector machine classifier\",\"authors\":\"Hussam Mustafa, Miloš Doroslova\",\"doi\":\"10.1109/ACSSC.2004.1399565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose four features to classify amplitude shift keying with two levels and four levels, binary phase shift keying, quadrature phase keying, frequency shift keying with two carriers and four carriers. After that we present a new method of classification based on support vector machine (SVM) that uses the four proposed features. We study the performance of SVM classifier and compare it to the previous work done in the literature on the digital modulation classification problem.\",\"PeriodicalId\":396779,\"journal\":{\"name\":\"Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004.\",\"volume\":\"151 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"35\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.2004.1399565\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.2004.1399565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digital modulation recognition using support vector machine classifier
We propose four features to classify amplitude shift keying with two levels and four levels, binary phase shift keying, quadrature phase keying, frequency shift keying with two carriers and four carriers. After that we present a new method of classification based on support vector machine (SVM) that uses the four proposed features. We study the performance of SVM classifier and compare it to the previous work done in the literature on the digital modulation classification problem.