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机构地区:[1]CollegeofPouerEngineering,UniversityofShanghaiforScienceandTechnology,Shanghai200093,China [2]PhysicalOceanographyLaboratory,OceanUniversityofQingdao,Qingdao266003,China
出 处:《Chinese Journal of Oceanology and Limnology》2001年第1期29-34,共6页中国海洋湖沼学报(英文版)
基 金:Project4 94 762 54supportedbyNSFC .
摘 要:A novel method is proposed to obtain the power spectra of hidden variables in a chaotic time series. By embedding the data in phase space , and recording the conditional probability density of points that the trajectory encounters as it evolves in the reconstructed phase space, it is possible to recover the power spectra of hidden variables in chaotic time series through a spectral analysis over the conditional probability density time series. The method is robust in the application to Lorenz system, 4 dimension Rssler system and rigid body motion by linear feedback system (LFRBM). Applying the method to the time series of sea surface temperature (SST) of the South China Sea, we obtained the power spectra of the wind speed (WS) from SST data. Furthermore, the results showed that there exists an important nonlinear interaction between the SST and the WS.A novel method is proposed to obtain the power spectra of hidden variables in a chaotic time series. By embedding the data in phase space , and recording the conditional probability density of points that the trajectory encounters as it evolves in the reconstructed phase space, it is possible to recover the power spectra of hidden variables in chaotic time series through a spectral analysis over the conditional probability density time series. The method is robust in the application to Lorenz system, 4 dimension Rssler system and rigid body motion by linear feedback system (LFRBM). Applying the method to the time series of sea surface temperature (SST) of the South China Sea, we obtained the power spectra of the wind speed (WS) from SST data. Furthermore, the results showed that there exists an important nonlinear interaction between the SST and the WS.
关 键 词:reconstructed phase space conditional probability density power spectraL
分 类 号:P733[天文地球—物理海洋学]
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