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A symplectic geometry-based method for nonlinear time series decomposition and prediction
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10.1063/1.4817181
/content/aip/journal/apl/103/5/10.1063/1.4817181
http://aip.metastore.ingenta.com/content/aip/journal/apl/103/5/10.1063/1.4817181

Figures

Image of FIG. 1.
FIG. 1.

component of Lorenz series, along with its eight reconstructed components by SGSA.

Image of FIG. 2.
FIG. 2.

component of noisy Lorenz series with 10% noise level, along with its eight reconstructed components by SGSA.

Image of FIG. 3.
FIG. 3.

Symplectic geometry spectra of clean and noisy Lorenz series with 2%, 5%, and 10% Gaussian noise.

Image of FIG. 4.
FIG. 4.

A Lorenz series with 5% Gaussian noise and its long-term prediction values by SGSA and local approximation.

Tables

Generic image for table
Table I.

Normalized mean squared errors of SGSA and local approximation predictions for the Lorenz series.

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/content/aip/journal/apl/103/5/10.1063/1.4817181
2013-07-31
2014-04-19
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: A symplectic geometry-based method for nonlinear time series decomposition and prediction
http://aip.metastore.ingenta.com/content/aip/journal/apl/103/5/10.1063/1.4817181
10.1063/1.4817181
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