{"title":"有限混合和隐马尔可夫模型状态估计的比较","authors":"I. Nagy, E. Suzdaleva, T. Mlynarova","doi":"10.1109/IDAACS.2011.6072822","DOIUrl":null,"url":null,"abstract":"Many various algorithms are developed for state estimation of dynamic switching systems. It is not a straightforward task to choose the most suitable one. This paper deals with testing of state estimation via two well-known approaches: recursive estimation with finite mixtures and iterative technique with hidden Markov models. A discussion of comparison of these online and offline counterparts is of true interest. The paper describes experiments providing a comparison of these methods.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of state estimation using finite mixtures and hidden Markov models\",\"authors\":\"I. Nagy, E. Suzdaleva, T. Mlynarova\",\"doi\":\"10.1109/IDAACS.2011.6072822\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many various algorithms are developed for state estimation of dynamic switching systems. It is not a straightforward task to choose the most suitable one. This paper deals with testing of state estimation via two well-known approaches: recursive estimation with finite mixtures and iterative technique with hidden Markov models. A discussion of comparison of these online and offline counterparts is of true interest. The paper describes experiments providing a comparison of these methods.\",\"PeriodicalId\":106306,\"journal\":{\"name\":\"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IDAACS.2011.6072822\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAACS.2011.6072822","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of state estimation using finite mixtures and hidden Markov models
Many various algorithms are developed for state estimation of dynamic switching systems. It is not a straightforward task to choose the most suitable one. This paper deals with testing of state estimation via two well-known approaches: recursive estimation with finite mixtures and iterative technique with hidden Markov models. A discussion of comparison of these online and offline counterparts is of true interest. The paper describes experiments providing a comparison of these methods.