{"title":"数据融合技术及其应用","authors":"Hai-rong Dong, David Evans","doi":"10.1109/FSKD.2007.237","DOIUrl":null,"url":null,"abstract":"This paper mainly describes the data-fusion techniques combining the data from two independent sensor systems with the aim of improving overall system performance. The data-fusion algorithms that form the core of the system are described in detail, together with the development work being undertaken. Using simulated data generated by a software model and real data, the analysis of improving system performance is discussed in detail.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Data-Fusion Techniques and Its Application\",\"authors\":\"Hai-rong Dong, David Evans\",\"doi\":\"10.1109/FSKD.2007.237\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper mainly describes the data-fusion techniques combining the data from two independent sensor systems with the aim of improving overall system performance. The data-fusion algorithms that form the core of the system are described in detail, together with the development work being undertaken. Using simulated data generated by a software model and real data, the analysis of improving system performance is discussed in detail.\",\"PeriodicalId\":201883,\"journal\":{\"name\":\"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FSKD.2007.237\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FSKD.2007.237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper mainly describes the data-fusion techniques combining the data from two independent sensor systems with the aim of improving overall system performance. The data-fusion algorithms that form the core of the system are described in detail, together with the development work being undertaken. Using simulated data generated by a software model and real data, the analysis of improving system performance is discussed in detail.