{"title":"精确递归最小二乘算法的ARMA建模","authors":"S. Prasad, S. Joshi","doi":"10.1109/ICASSP.1987.1169813","DOIUrl":null,"url":null,"abstract":"The present paper aims to present an entirely new approach for the development of \"exact\" recursive least squares algorithms for ARMA filtering and modeling when the inputs (asssumed here to be \"white\") are not observable. The approach is heavily based on the recently proposed \"predictor-space\" representation of ARMA processes 131 and theu se of some new, moreg eneral projection operator update formulas, breifly summarized here.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Exact recursive least squares algorithms for ARMA modeling\",\"authors\":\"S. Prasad, S. Joshi\",\"doi\":\"10.1109/ICASSP.1987.1169813\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The present paper aims to present an entirely new approach for the development of \\\"exact\\\" recursive least squares algorithms for ARMA filtering and modeling when the inputs (asssumed here to be \\\"white\\\") are not observable. The approach is heavily based on the recently proposed \\\"predictor-space\\\" representation of ARMA processes 131 and theu se of some new, moreg eneral projection operator update formulas, breifly summarized here.\",\"PeriodicalId\":140810,\"journal\":{\"name\":\"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1987-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.1987.1169813\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.1987.1169813","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exact recursive least squares algorithms for ARMA modeling
The present paper aims to present an entirely new approach for the development of "exact" recursive least squares algorithms for ARMA filtering and modeling when the inputs (asssumed here to be "white") are not observable. The approach is heavily based on the recently proposed "predictor-space" representation of ARMA processes 131 and theu se of some new, moreg eneral projection operator update formulas, breifly summarized here.
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