{"title":"使用非线性最小二乘的z域多项式的谱分解","authors":"T. Moir","doi":"10.1109/ICDSP.2014.6900705","DOIUrl":null,"url":null,"abstract":"A new recursive method for spectral factorizing polynomials is given. The method uses non-linear least-squares. The method is simple to implement and has applications in many areas of adaptive filtering, system identification and control. The optimization method is not new but to date has not been applied to spectral factorization. Convergence is much faster than ordinary root finding algorithms. (superlinear versus quadratic).","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spectral factorization of z-domain polynomials using non-linear least-squares\",\"authors\":\"T. Moir\",\"doi\":\"10.1109/ICDSP.2014.6900705\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new recursive method for spectral factorizing polynomials is given. The method uses non-linear least-squares. The method is simple to implement and has applications in many areas of adaptive filtering, system identification and control. The optimization method is not new but to date has not been applied to spectral factorization. Convergence is much faster than ordinary root finding algorithms. (superlinear versus quadratic).\",\"PeriodicalId\":301856,\"journal\":{\"name\":\"2014 19th International Conference on Digital Signal Processing\",\"volume\":\"108 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 19th International Conference on Digital Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDSP.2014.6900705\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 19th International Conference on Digital Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSP.2014.6900705","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spectral factorization of z-domain polynomials using non-linear least-squares
A new recursive method for spectral factorizing polynomials is given. The method uses non-linear least-squares. The method is simple to implement and has applications in many areas of adaptive filtering, system identification and control. The optimization method is not new but to date has not been applied to spectral factorization. Convergence is much faster than ordinary root finding algorithms. (superlinear versus quadratic).