{"title":"利用互信息对Sig53数据集进行调制识别","authors":"B. Comar","doi":"10.1109/WOCC58016.2023.10139391","DOIUrl":null,"url":null,"abstract":"This paper discusses an approach to classification (modulation recognition) of RF signals based on mutual information calculations. A small amount of labeled (representative) signals from each source are used by the classification system when determining the class of an unknown (test) signal. This method may be useful in scenarios where labeled data is unavailable in significant quantities.","PeriodicalId":226792,"journal":{"name":"2023 32nd Wireless and Optical Communications Conference (WOCC)","volume":"45 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Using Mutual Information to Perform Modulation Recognition on the Sig53 Dataset\",\"authors\":\"B. Comar\",\"doi\":\"10.1109/WOCC58016.2023.10139391\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper discusses an approach to classification (modulation recognition) of RF signals based on mutual information calculations. A small amount of labeled (representative) signals from each source are used by the classification system when determining the class of an unknown (test) signal. This method may be useful in scenarios where labeled data is unavailable in significant quantities.\",\"PeriodicalId\":226792,\"journal\":{\"name\":\"2023 32nd Wireless and Optical Communications Conference (WOCC)\",\"volume\":\"45 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 32nd Wireless and Optical Communications Conference (WOCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOCC58016.2023.10139391\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 32nd Wireless and Optical Communications Conference (WOCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOCC58016.2023.10139391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Mutual Information to Perform Modulation Recognition on the Sig53 Dataset
This paper discusses an approach to classification (modulation recognition) of RF signals based on mutual information calculations. A small amount of labeled (representative) signals from each source are used by the classification system when determining the class of an unknown (test) signal. This method may be useful in scenarios where labeled data is unavailable in significant quantities.