Predicting Spatio-Temporal Time Series Using Dimension Reduced Local States

12 Apr 2019 · Isensee Jonas, Datseris George, Parlitz Ulrich ·

We present a method for both cross estimation and iterated time series prediction of spatio temporal dynamics based on reconstructed local states, PCA dimension reduction, and local modelling using nearest neighbour methods. The effectiveness of this approach is shown for (noisy) data from a (cubic) Barkley model, the Bueno-Orovio-Cherry-Fenton model, and the Kuramoto-Sivashinsky model.

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Predicting Spatio-Temporal Time Series Using Dimension Reduced Local States

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