{"title":"基于高阶统计量的m序列识别自适应智能阈值","authors":"M. Gouda, Yasser Ali","doi":"10.1109/UKSIM.2009.33","DOIUrl":null,"url":null,"abstract":"In digital communication systems, the Higher Order Statistical Techniques (HOS) can be used for data recovery and recognition, In this paper, the process of developing the output of the Triple Correlation Function (TCF) using different threshold techniques will be highlighted, and a study of the effect of using the fixed and the adaptive threshold techniques in noisy environment will be performed.","PeriodicalId":327522,"journal":{"name":"2009 11th International Conference on Computer Modelling and Simulation","volume":"151 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Adaptive and Smart Threshold for M-sequence Identification Using Higher Order Statistics\",\"authors\":\"M. Gouda, Yasser Ali\",\"doi\":\"10.1109/UKSIM.2009.33\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In digital communication systems, the Higher Order Statistical Techniques (HOS) can be used for data recovery and recognition, In this paper, the process of developing the output of the Triple Correlation Function (TCF) using different threshold techniques will be highlighted, and a study of the effect of using the fixed and the adaptive threshold techniques in noisy environment will be performed.\",\"PeriodicalId\":327522,\"journal\":{\"name\":\"2009 11th International Conference on Computer Modelling and Simulation\",\"volume\":\"151 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 11th International Conference on Computer Modelling and Simulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UKSIM.2009.33\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 11th International Conference on Computer Modelling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UKSIM.2009.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive and Smart Threshold for M-sequence Identification Using Higher Order Statistics
In digital communication systems, the Higher Order Statistical Techniques (HOS) can be used for data recovery and recognition, In this paper, the process of developing the output of the Triple Correlation Function (TCF) using different threshold techniques will be highlighted, and a study of the effect of using the fixed and the adaptive threshold techniques in noisy environment will be performed.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
