C. Shao, Qingqing Liu, Tingting Wang, Binghong Wang
{"title":"Estimating properties of chaotic system based on S-NURBS resampling method","authors":"C. Shao, Qingqing Liu, Tingting Wang, Binghong Wang","doi":"10.1109/MIC.2013.6757994","DOIUrl":null,"url":null,"abstract":"Physical properties of the chaotic system play important roles on studying the innate character and deciding the practical predictability of the dynamics. For a short piece of undersampled chaotic signals, it is very hard to abstract the physical properties of the signal source from the sequence. In this paper, we model this type of data with global S-NURBS method to reconstruct a smooth trajectory and resample the trajectory to get enough series. In this way, the problem of estimating the physical properties from small undersampled data is turned to the work of calculating the properties of the resampled time series. The new interpolation method is named as S-NURBS resampling method, and the simulation experiment demonstrates that the new method has a good performance in studying physical systems from the observed time series.","PeriodicalId":404630,"journal":{"name":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIC.2013.6757994","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Physical properties of the chaotic system play important roles on studying the innate character and deciding the practical predictability of the dynamics. For a short piece of undersampled chaotic signals, it is very hard to abstract the physical properties of the signal source from the sequence. In this paper, we model this type of data with global S-NURBS method to reconstruct a smooth trajectory and resample the trajectory to get enough series. In this way, the problem of estimating the physical properties from small undersampled data is turned to the work of calculating the properties of the resampled time series. The new interpolation method is named as S-NURBS resampling method, and the simulation experiment demonstrates that the new method has a good performance in studying physical systems from the observed time series.