{"title":"连续时间过程的固定区间平滑","authors":"J. Wall, A. Willsky, N. Sandell","doi":"10.1109/CDC.1980.271822","DOIUrl":null,"url":null,"abstract":"A \"first principles\" argument is used to obtain the Mayne-Fraser two-filter smoother. The built-in asymmetry of the Mayne-Fraser smoother is pointed out, and it is shown how the asymmetry may be removed. Reversed-time Markov models play a key role here in forming a state estimate from future observations.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The fixed-interval smoother for continuous-time processes\",\"authors\":\"J. Wall, A. Willsky, N. Sandell\",\"doi\":\"10.1109/CDC.1980.271822\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A \\\"first principles\\\" argument is used to obtain the Mayne-Fraser two-filter smoother. The built-in asymmetry of the Mayne-Fraser smoother is pointed out, and it is shown how the asymmetry may be removed. Reversed-time Markov models play a key role here in forming a state estimate from future observations.\",\"PeriodicalId\":332964,\"journal\":{\"name\":\"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1980-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1980.271822\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1980.271822","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The fixed-interval smoother for continuous-time processes
A "first principles" argument is used to obtain the Mayne-Fraser two-filter smoother. The built-in asymmetry of the Mayne-Fraser smoother is pointed out, and it is shown how the asymmetry may be removed. Reversed-time Markov models play a key role here in forming a state estimate from future observations.