複雜訊號之決定論性測試與噪音強度估計
碩士 === 國立中山大學 === 物理學系 === 85 === We address the issue of recognizing determinism in a time series. Specifically, we employ the method of singular-value-decomposition (SVD) to derive the eigenvalue spectra of the trajectory matrices constructed from a number of scalar time series, mainly white...
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| Format: | Others |
| Language: | en_US |
| Published: |
1997
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| Online Access: | http://ndltd.ncl.edu.tw/handle/22876582887129074426 |
| Summary: | 碩士 === 國立中山大學 === 物理學系 === 85 ===
We address the issue of recognizing determinism in a time series. Specifically, we employ the method of singular-value-decomposition (SVD) to derive the eigenvalue spectra of the trajectory matrices constructed from a number of scalar time series, mainly white noise and chaotic signals, where a very large embedding dimension is used. Several numerical examples and a nonlinear diode electronic experiment are provided. The results suggest that the SVD eigenvalue spectrum can be employed as a measure of determinism and an estimate for the strength of a noise contained in the time series can be deduced. A new phenomenon of the so-called noise-induced coherence which is caused-by-the variable-dependent-dynamical, noise in the diode resonator is also presented.
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