{"title":"An Adaptive Orthogonal SSA Decomposition Algorithm for a Time Series","authors":"K. Kume, N. Nose-Togawa","doi":"10.1142/S2424922X1850002X","DOIUrl":null,"url":null,"abstract":"Singular spectrum analysis (SSA) is a nonparametric spectral decomposition of a time series into arbitrary number of interpretable components. It involves a single parameter, window length L, which...","PeriodicalId":47145,"journal":{"name":"Advances in Data Science and Adaptive Analysis","volume":"36 1","pages":"1850002:1-1850002:15"},"PeriodicalIF":0.5000,"publicationDate":"2018-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Data Science and Adaptive Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/S2424922X1850002X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 2
Abstract
Singular spectrum analysis (SSA) is a nonparametric spectral decomposition of a time series into arbitrary number of interpretable components. It involves a single parameter, window length L, which...
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