{"title":"基于信息熵和灰色关联分析的信号识别方法研究","authors":"Xuhong Yin, Yun Lin, Z. Dou","doi":"10.1109/ICEICT.2016.7879724","DOIUrl":null,"url":null,"abstract":"In this paper, we base the grey relational analysis and interval number as a method for recognizing the digital signal modulation. Firstly, the wavelet energy spectrum entropy, power spectrum entropy and bispectral entropy are selected as the characteristic of the signal modulation type. Then, considering the situation of the received signal is not stable, this paper combined the idea of interval number with the sequences of the grey relational analysis. Finally, this paper analyzed the recognition results of the classical grey relational analysis and grey relational analysis based on the interval number theory. The simulation experiment indicates that the grey relational analysis can be applied to the communication signal modulation recognition.","PeriodicalId":224387,"journal":{"name":"2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The method research of signal recognition based on information entropy and grey relational analysis\",\"authors\":\"Xuhong Yin, Yun Lin, Z. Dou\",\"doi\":\"10.1109/ICEICT.2016.7879724\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we base the grey relational analysis and interval number as a method for recognizing the digital signal modulation. Firstly, the wavelet energy spectrum entropy, power spectrum entropy and bispectral entropy are selected as the characteristic of the signal modulation type. Then, considering the situation of the received signal is not stable, this paper combined the idea of interval number with the sequences of the grey relational analysis. Finally, this paper analyzed the recognition results of the classical grey relational analysis and grey relational analysis based on the interval number theory. The simulation experiment indicates that the grey relational analysis can be applied to the communication signal modulation recognition.\",\"PeriodicalId\":224387,\"journal\":{\"name\":\"2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEICT.2016.7879724\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEICT.2016.7879724","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The method research of signal recognition based on information entropy and grey relational analysis
In this paper, we base the grey relational analysis and interval number as a method for recognizing the digital signal modulation. Firstly, the wavelet energy spectrum entropy, power spectrum entropy and bispectral entropy are selected as the characteristic of the signal modulation type. Then, considering the situation of the received signal is not stable, this paper combined the idea of interval number with the sequences of the grey relational analysis. Finally, this paper analyzed the recognition results of the classical grey relational analysis and grey relational analysis based on the interval number theory. The simulation experiment indicates that the grey relational analysis can be applied to the communication signal modulation recognition.
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