Keyword : time series prediction


Using a Single Dendritic Neuron to Forecast Tourist Arrivals to Japan
Wei CHEN Jian SUN Shangce GAO Jiu-Jun CHENG Jiahai WANG Yuki TODO 
Publication:   
Publication Date: 2017/01/01
Vol. E100-D  No. 1 ; pp. 190-202
Type of Manuscript:  PAPER
Category: Biocybernetics, Neurocomputing
Keyword: 
artificial neural networkschaosdendritic neuron modelphase space reconstructiontime series predictiontourism demand
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A Novel Double Oscillation Model for Prediction of fMRI BOLD Signals without Detrending
Takashi MATSUBARA Hiroyuki TORIKAI Tetsuya SHIMOKAWA Kenji LEIBNITZ Ferdinand PEPER 
Publication:   IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2015/09/01
Vol. E98-A  No. 9 ; pp. 1924-1936
Type of Manuscript:  PAPER
Category: Nonlinear Problems
Keyword: 
functional Magnetic Resonance Imagingnonlinear dynamical systemtime series prediction
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Generalized Regularization Networks with a Particular Class of Bell-Shaped Basis Function
Akira NAGAMI Hirofumi INADA Takaya MIYANO 
Publication:   IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1998/11/25
Vol. E81-A  No. 11 ; pp. 2443-2448
Type of Manuscript:  PAPER
Category: Neural Networks
Keyword: 
radial basis function networkneural networkneuro devicechaostime series prediction
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A Cascade Form Predictor of Neural and FIR Filters and Its Minimum Size Estimation Based on Nonlinearity Analysis of Time Series
Ashraf A. M. KHALAF Kenji NAKAYAMA 
Publication:   IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1998/03/25
Vol. E81-A  No. 3 ; pp. 364-373
Type of Manuscript:  Special Section PAPER (Special Section of Selected Papers from the 10th Karuizawa Workshop on Circuits and Systems)
Category: 
Keyword: 
cascade form predictortime series predictionmulti-layer neural networksFIR filters nonlinear predictionnonlinearity analysisinput dimension estimation
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A Prediction Method of Non-Stationary Time Series Data by Using a Modular Structured Neural Network
Eiji WATANABE Noboru NAKASAKO Yasuo MITANI 
Publication:   IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1997/06/25
Vol. E80-A  No. 6 ; pp. 971-976
Type of Manuscript:  Special Section PAPER (Special Section on Signal Processing Theories and Applications Based on Modelling of Nonstationary Processes)
Category: 
Keyword: 
AR model with time varying paramenterstime series predictionmodular structured neural networksadditive learning ability
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