{"title":"时变非线性系统的简约基序列逼近","authors":"Matthew Green, A. Zoubir","doi":"10.1109/ISCAS.2000.857048","DOIUrl":null,"url":null,"abstract":"An approach for identifying time-varying nonlinear systems is presented. The time-variation of the system is approximated by a weighted combination of sequences from a given basis. In this case, to identify the system it is sufficient to estimate the time-invariant coefficients of the sequences. The focus of our investigation is on selecting these sequences to use in the approximation. We propose using a search method to determine which sequences contribute significantly to the approximation and thus lead to a parsimonious model that is able to characterise the system dynamics and time-variation together.","PeriodicalId":6422,"journal":{"name":"2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)","volume":"176 1","pages":"148-151 vol.1"},"PeriodicalIF":0.0000,"publicationDate":"2000-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A search for a parsimonious basis sequence approximation of time-varying, nonlinear systems\",\"authors\":\"Matthew Green, A. Zoubir\",\"doi\":\"10.1109/ISCAS.2000.857048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approach for identifying time-varying nonlinear systems is presented. The time-variation of the system is approximated by a weighted combination of sequences from a given basis. In this case, to identify the system it is sufficient to estimate the time-invariant coefficients of the sequences. The focus of our investigation is on selecting these sequences to use in the approximation. We propose using a search method to determine which sequences contribute significantly to the approximation and thus lead to a parsimonious model that is able to characterise the system dynamics and time-variation together.\",\"PeriodicalId\":6422,\"journal\":{\"name\":\"2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)\",\"volume\":\"176 1\",\"pages\":\"148-151 vol.1\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCAS.2000.857048\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAS.2000.857048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A search for a parsimonious basis sequence approximation of time-varying, nonlinear systems
An approach for identifying time-varying nonlinear systems is presented. The time-variation of the system is approximated by a weighted combination of sequences from a given basis. In this case, to identify the system it is sufficient to estimate the time-invariant coefficients of the sequences. The focus of our investigation is on selecting these sequences to use in the approximation. We propose using a search method to determine which sequences contribute significantly to the approximation and thus lead to a parsimonious model that is able to characterise the system dynamics and time-variation together.
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