{"title":"分布非参数检测的一些结果","authors":"J. Han, P. Varshney, V. Vannicola","doi":"10.1109/CDC.1990.203266","DOIUrl":null,"url":null,"abstract":"The application of nonparametric techniques in distributed detection systems is investigated. Sign detectors and dead-zone limiter detectors are considered. Generalized Gaussian distribution is used as the input statistics, which is a general class of symmetric unimodal univariate probability density functions. Performance comparisons between nonparametric distributed detectors and some parametric distributed detectors are given.<<ETX>>","PeriodicalId":287089,"journal":{"name":"29th IEEE Conference on Decision and Control","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Some results on distributed nonparametric detection\",\"authors\":\"J. Han, P. Varshney, V. Vannicola\",\"doi\":\"10.1109/CDC.1990.203266\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The application of nonparametric techniques in distributed detection systems is investigated. Sign detectors and dead-zone limiter detectors are considered. Generalized Gaussian distribution is used as the input statistics, which is a general class of symmetric unimodal univariate probability density functions. Performance comparisons between nonparametric distributed detectors and some parametric distributed detectors are given.<<ETX>>\",\"PeriodicalId\":287089,\"journal\":{\"name\":\"29th IEEE Conference on Decision and Control\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"29th IEEE Conference on Decision and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1990.203266\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"29th IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1990.203266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Some results on distributed nonparametric detection
The application of nonparametric techniques in distributed detection systems is investigated. Sign detectors and dead-zone limiter detectors are considered. Generalized Gaussian distribution is used as the input statistics, which is a general class of symmetric unimodal univariate probability density functions. Performance comparisons between nonparametric distributed detectors and some parametric distributed detectors are given.<>