{"title":"单纯基于输出序列的初等双线性时间序列模型的可逆性条件","authors":"Lukasz Malinski","doi":"10.1109/MMAR.2011.6031366","DOIUrl":null,"url":null,"abstract":"Reversibility of elementary bilinear time-series model is very important issue in parametric model identification based on minimisation of mean square value of prediction error. The reason is that estimation of parameters of irreversible time-series model is irreversible it is difficult. There is already very well known mathematical reversibility condition expressed as a function of the model's coefficient, which has to be identified. The paper contains a discussion of simple condition, which can provide information about model's reversibility before its identification.","PeriodicalId":440376,"journal":{"name":"2011 16th International Conference on Methods & Models in Automation & Robotics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The reversibility condition for elementary bilinear time-series model based on output sequence alone\",\"authors\":\"Lukasz Malinski\",\"doi\":\"10.1109/MMAR.2011.6031366\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reversibility of elementary bilinear time-series model is very important issue in parametric model identification based on minimisation of mean square value of prediction error. The reason is that estimation of parameters of irreversible time-series model is irreversible it is difficult. There is already very well known mathematical reversibility condition expressed as a function of the model's coefficient, which has to be identified. The paper contains a discussion of simple condition, which can provide information about model's reversibility before its identification.\",\"PeriodicalId\":440376,\"journal\":{\"name\":\"2011 16th International Conference on Methods & Models in Automation & Robotics\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 16th International Conference on Methods & Models in Automation & Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMAR.2011.6031366\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 16th International Conference on Methods & Models in Automation & Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR.2011.6031366","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The reversibility condition for elementary bilinear time-series model based on output sequence alone
Reversibility of elementary bilinear time-series model is very important issue in parametric model identification based on minimisation of mean square value of prediction error. The reason is that estimation of parameters of irreversible time-series model is irreversible it is difficult. There is already very well known mathematical reversibility condition expressed as a function of the model's coefficient, which has to be identified. The paper contains a discussion of simple condition, which can provide information about model's reversibility before its identification.