{"title":"单传感器检测与多源高阶光谱分类","authors":"M. Dogan, J. Mendel","doi":"10.1109/SSAP.1992.246819","DOIUrl":null,"url":null,"abstract":"A method to detect the number of nonGaussian sources is distinguished by its ability to perform detection with single sensor data, and is blind to Gaussian observation noise. After the detection procedure, the authors propose an algorithm for classification of sources employing a prior knowledge of their spectra. Simulation results indicate the performance of the algorithms.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Single sensor detection and classification of multiple sources by higher-order spectra\",\"authors\":\"M. Dogan, J. Mendel\",\"doi\":\"10.1109/SSAP.1992.246819\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method to detect the number of nonGaussian sources is distinguished by its ability to perform detection with single sensor data, and is blind to Gaussian observation noise. After the detection procedure, the authors propose an algorithm for classification of sources employing a prior knowledge of their spectra. Simulation results indicate the performance of the algorithms.<<ETX>>\",\"PeriodicalId\":309407,\"journal\":{\"name\":\"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSAP.1992.246819\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSAP.1992.246819","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Single sensor detection and classification of multiple sources by higher-order spectra
A method to detect the number of nonGaussian sources is distinguished by its ability to perform detection with single sensor data, and is blind to Gaussian observation noise. After the detection procedure, the authors propose an algorithm for classification of sources employing a prior knowledge of their spectra. Simulation results indicate the performance of the algorithms.<>