{"title":"Nonlinear dynamics techniques in signal processing","authors":"J. Parish","doi":"10.1109/SSAP.1992.246893","DOIUrl":null,"url":null,"abstract":"This paper describes the calculation of Lyapunov exponents and fractal dimension for a chaotic time series. These metrics provide appropriate characterization for the nonperiodic signals generated by low dimensional nonlinear systems. Nonlinear dynamics account for the underlying ergodicity of the nonlinear system which produces such signals. Results for several nonlinear systems are presented.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSAP.1992.246893","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper describes the calculation of Lyapunov exponents and fractal dimension for a chaotic time series. These metrics provide appropriate characterization for the nonperiodic signals generated by low dimensional nonlinear systems. Nonlinear dynamics account for the underlying ergodicity of the nonlinear system which produces such signals. Results for several nonlinear systems are presented.<>
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