{"title":"识别包含未知信号的预定随机信号","authors":"V. Bezruk","doi":"10.1109/CAMAP.2005.1574218","DOIUrl":null,"url":null,"abstract":"Some practical peculiarities of random signals recognition methods are considered for non-traditional cases when the signals with unknown probabilistic characteristics are presented for recognition along with the signals predetermined in a probabilistic sense. The distinctive peculiarities of the present work is that it considers the solution signals recognition problem on the basis of different probabilistic models - in the form of autoregression processes, mixtures of standard distributions, expansions in orthogonal functions of random signals. The data on decision of recognition problems are considered. In particular, that is decision the different problems of recognition signals for radio control, recognition of any types of targets by signals features using narrow-bend signals and recognition signals for medical diagnostic","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"131 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Recognition of the predetermined random signals involving the unknown signals\",\"authors\":\"V. Bezruk\",\"doi\":\"10.1109/CAMAP.2005.1574218\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Some practical peculiarities of random signals recognition methods are considered for non-traditional cases when the signals with unknown probabilistic characteristics are presented for recognition along with the signals predetermined in a probabilistic sense. The distinctive peculiarities of the present work is that it considers the solution signals recognition problem on the basis of different probabilistic models - in the form of autoregression processes, mixtures of standard distributions, expansions in orthogonal functions of random signals. The data on decision of recognition problems are considered. In particular, that is decision the different problems of recognition signals for radio control, recognition of any types of targets by signals features using narrow-bend signals and recognition signals for medical diagnostic\",\"PeriodicalId\":281761,\"journal\":{\"name\":\"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.\",\"volume\":\"131 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAMAP.2005.1574218\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMAP.2005.1574218","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognition of the predetermined random signals involving the unknown signals
Some practical peculiarities of random signals recognition methods are considered for non-traditional cases when the signals with unknown probabilistic characteristics are presented for recognition along with the signals predetermined in a probabilistic sense. The distinctive peculiarities of the present work is that it considers the solution signals recognition problem on the basis of different probabilistic models - in the form of autoregression processes, mixtures of standard distributions, expansions in orthogonal functions of random signals. The data on decision of recognition problems are considered. In particular, that is decision the different problems of recognition signals for radio control, recognition of any types of targets by signals features using narrow-bend signals and recognition signals for medical diagnostic