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Abstract
According to the Takens theorem, we reconstruct the chaotic time series to multivariate data and use the multivariate local polynomial estimator to predict the chaotic time series. This kernel estimator has the advantages of both the local model and the global model. The simulation shows that the estimator can predict the chaotic time series accurately.

Keywords:
chaotic time series/

multivariate local polynomial regression/

kernel estimator
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Cited By

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[3]	Li Jun, Zhang You-Peng.Single-step and multiple-step prediction of chaotic time series using Gaussian process model. Acta Physica Sinica, 2011, 60(7): 070513.doi:10.7498/aps.60.070513
[4]	Zhang Xian, Wang Hong-Li.Incremental regularized extreme learning machine based on Cholesky factorization and its application to time series prediction. Acta Physica Sinica, 2011, 60(11): 110201.doi:10.7498/aps.60.110201
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Vol. 56, Issue 12 - 2007-06-20

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