Time series prediction using a hybrid model of neural network and FIR filter

Time series prediction using a hybrid model of neural network and FIR filter

フォーマット:

論文

責任表示:

Khalaf, Ashraf A.M. ; Nakayama, Kenji

言語:

英語

出版情報:

IEEE(Institute of Electrical and Electronics Engineers), 1998-05-01

著者名:

掲載情報:

IEEE International Conference on Neural Networks - Conference Proceedings

ISSN:

1098-7576

巻:

3

開始ページ:

1975

終了ページ:

1980

バージョン:

publisher

概要:

Time series prediction is a very important technology in a wide variety of field. The actual time series contains both linear and nonlinear properties. The amplitude of the time series to be predicted is usually continuous value. For this reason, we combine nonlinear and linear predictors in a cascade form. In order to estimate the minimum size of the proposed predictor, we propose a nonlinearity analysis for the time series of interest. Computer simulations … using the sunspot data have demonstrated the efficiency of the proposed predictor and the nonlinearity analysis. 続きを見る

URL:

http://hdl.handle.net/2297/6783

タイトル・著者・出版者が同じ資料

詳細

主題:	Computer simulation; FIR filters; Multilayer neural networks; Nonlinearity analysis method; Time series analysis
受理日:	1998-05-01

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