{"title":"双线性随机系统的可辨识性","authors":"C. Bourin, P. Bondon","doi":"10.1109/HOST.1997.613511","DOIUrl":null,"url":null,"abstract":"Bilinear systems are useful to model nonlinear time series. They can be described by a nonlinear recursive equation involving a finite number of parameters. Their analysis and particularly the estimation of the parameters is of central interest. In this paper we establish difference equations between lagged moments and cumulants up to third-order of a simple bilinear model, and show how to use these relations to estimate the parameters.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"On the identifiability of bilinear stochastic systems\",\"authors\":\"C. Bourin, P. Bondon\",\"doi\":\"10.1109/HOST.1997.613511\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bilinear systems are useful to model nonlinear time series. They can be described by a nonlinear recursive equation involving a finite number of parameters. Their analysis and particularly the estimation of the parameters is of central interest. In this paper we establish difference equations between lagged moments and cumulants up to third-order of a simple bilinear model, and show how to use these relations to estimate the parameters.\",\"PeriodicalId\":305928,\"journal\":{\"name\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HOST.1997.613511\",\"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 IEEE Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1997.613511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the identifiability of bilinear stochastic systems
Bilinear systems are useful to model nonlinear time series. They can be described by a nonlinear recursive equation involving a finite number of parameters. Their analysis and particularly the estimation of the parameters is of central interest. In this paper we establish difference equations between lagged moments and cumulants up to third-order of a simple bilinear model, and show how to use these relations to estimate the parameters.
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