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Please use this identifier to cite or link to this item: http://hdl.handle.net/10561/196

Title: 局所近似法によるカオス時系列データの予測
Other Titles: Predicting Chaotic Time Series based on a Local Approximation Technique
Author: 伊藤, 憲一
Author's alias: ITOH, Ken-ichi
Issue Date: 20-Dec-2006
Publisher: 県立長崎シーボルト大学
Shimei: 県立長崎シーボルト大学国際情報学部紀要
Issue: 7
ISSN: 1346-6372
Abstract: A Method is presented for predicting chaotic time series based on a local approximation technique. In the local approximation technique, a state space is reconstructed from a time series using delay coordinate embedding and then a local predictor is constructed on the basis of the motion of the nearest neighbors in the state space. The parameters, such as the embedding dimension and the number of the nearest neighbors,have a significant effect on the prediction accuracy. The method can be used as a means of choosing the parameters suitable for the prediction. The efficacy of the method is demonstrated using chaotic time series generated by the Hénon map and the Ikeda map.
Keywords: 局所近似法,カオス,時系列,chaos,time series,prediction,embedding,dimension
Description: 国立情報学研究所により電子化
URI: http://hdl.handle.net/10561/196
Appears in Collections:第7号

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