{"title":"深度学习方法在先验不确定性和随机干扰条件下部分可观测子图识别中的应用(以星座识别问题为例)","authors":"V. Galkin, A. Makarenko","doi":"10.1007/978-3-030-83266-7_21","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":304147,"journal":{"name":"Recent Developments in Stochastic Methods and Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of Deep Learning Methods for the Identification of Partially Observable Subgraphs Under the Conditions of a Priori Uncertainty and Stochastic Disturbances (Using the Example of the Problem of Recognizing Constellations)\",\"authors\":\"V. Galkin, A. Makarenko\",\"doi\":\"10.1007/978-3-030-83266-7_21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":304147,\"journal\":{\"name\":\"Recent Developments in Stochastic Methods and Applications\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Recent Developments in Stochastic Methods and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/978-3-030-83266-7_21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Recent Developments in Stochastic Methods and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-030-83266-7_21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Deep Learning Methods for the Identification of Partially Observable Subgraphs Under the Conditions of a Priori Uncertainty and Stochastic Disturbances (Using the Example of the Problem of Recognizing Constellations)