{"title":"基于辅助模型和FIRmode的双速率Box-Jenkins模型随机梯度算法","authors":"Jing Chen, Ruifeng Ding","doi":"10.1631/jzus.C1300072","DOIUrl":null,"url":null,"abstract":"Based on the work in Ding and Ding (2008), we develop a modified stochastic gradient (SG) parameter estimation algorithm for a dual-rate Box-Jenkins model by using an auxiliary model. We simplify the complex dual-rate Box-Jenkins model to two finite impulse response (FIR) models, present an auxiliary model to estimate the missing outputs and the unknown noise variables, and compute all the unknown parameters of the system with colored noises. Simulation results indicate that the proposed method is effective.","PeriodicalId":49947,"journal":{"name":"Journal of Zhejiang University-Science C-Computers & Electronics","volume":"15 1","pages":"147-152"},"PeriodicalIF":0.0000,"publicationDate":"2014-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1631/jzus.C1300072","citationCount":"5","resultStr":"{\"title\":\"Stochastic gradient algorithm for a dual-rate Box-Jenkins model based on auxiliary model and FIRmode\",\"authors\":\"Jing Chen, Ruifeng Ding\",\"doi\":\"10.1631/jzus.C1300072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the work in Ding and Ding (2008), we develop a modified stochastic gradient (SG) parameter estimation algorithm for a dual-rate Box-Jenkins model by using an auxiliary model. We simplify the complex dual-rate Box-Jenkins model to two finite impulse response (FIR) models, present an auxiliary model to estimate the missing outputs and the unknown noise variables, and compute all the unknown parameters of the system with colored noises. Simulation results indicate that the proposed method is effective.\",\"PeriodicalId\":49947,\"journal\":{\"name\":\"Journal of Zhejiang University-Science C-Computers & Electronics\",\"volume\":\"15 1\",\"pages\":\"147-152\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-02-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1631/jzus.C1300072\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Zhejiang University-Science C-Computers & Electronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1631/jzus.C1300072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Zhejiang University-Science C-Computers & Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1631/jzus.C1300072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
摘要
在Ding and Ding(2008)的基础上，我们利用辅助模型开发了一种改进的双速率Box-Jenkins模型的随机梯度(SG)参数估计算法。我们将复杂的双速率Box-Jenkins模型简化为两个有限脉冲响应(FIR)模型，提出了一个辅助模型来估计缺失输出和未知噪声变量，并计算了带有彩色噪声的系统的所有未知参数。仿真结果表明，该方法是有效的。
Stochastic gradient algorithm for a dual-rate Box-Jenkins model based on auxiliary model and FIRmode
Based on the work in Ding and Ding (2008), we develop a modified stochastic gradient (SG) parameter estimation algorithm for a dual-rate Box-Jenkins model by using an auxiliary model. We simplify the complex dual-rate Box-Jenkins model to two finite impulse response (FIR) models, present an auxiliary model to estimate the missing outputs and the unknown noise variables, and compute all the unknown parameters of the system with colored noises. Simulation results indicate that the proposed method is effective.
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