کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9868029 | 1530678 | 2005 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Identification determinism in time series based on symplectic geometry spectra
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
فیزیک و نجوم (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Identification determinism in time series based on symplectic geometry spectra Identification determinism in time series based on symplectic geometry spectra](/preview/png/9868029.png)
چکیده انگلیسی
A new method based upon combination symplectic geometry spectra (SGS) with surrogate data analysis is proposed to identify its deterministic chaoticity or the stochastic nature from a scalar time series. Compared with the singular value decomposition (SVD), symplectic similar transform is nonlinear and has measure preserving characteristic, so the SGS can keep the essential character of the original time series. The power of the proposed algorithm to differentiate between deterministic, especially high-dimensional deterministic, and stochastic dynamics is tested on several numerically generated time series.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physics Letters A - Volume 342, Issues 1â2, 4 July 2005, Pages 156-161
Journal: Physics Letters A - Volume 342, Issues 1â2, 4 July 2005, Pages 156-161
نویسندگان
Hongbo Xie, Zhizhong Wang, Hai Huang,