Time Series Identifying and Modeling with Neural Networks

Proceedings of the International Joint Conference on Neural Networks

Volumn 4, Issue , 2003, Pages 2454-2459

  Gao, Dayong ^a   Kinouchi, Y ^a   Ito, K ^a   Zhao, Xueli ^b  

^a UNIVERSITY OF TOKUSHIMA   (Japan)

^b CLIN RESEARCH INSTITUTE OF MONTREAL   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; FINANCIAL DATA PROCESSING; TIME SERIES ANALYSIS;

HOMEOSTATIC DYNAMICS;

NEURAL NETWORKS;

EID: 0141719909     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Weigend, A., Huberman, B. and Rumelhart, D., "Predicting the future: a connectionist approach," International Journal of Neural Systems, 1-3, 193-209 (1990).
2. Rogers, R. and Vemuri, V., "Time series and forecasting problem," in Rogers, R. and Vemuri, V. (Eds), Artificial Neural Networks: Forecasting Time series, IEEE Computer Society Press, New York (1994).
3. Apostolos-Paul N. Refenes, A. Neil Burgess, and Yves Bentz, "Neural Networks in Financial Engineering: A Study in Methodology," IEEE Transactions on Neural Networks, 8-6, 1222-1267 (1997).
4. Hopfield, J., "Neural networks and physical systems with emergent collective computational abilities," Proc. Nat. Acad. Sci., 79-8, 2554-8 (1982).
5. Haykin, S., Neural Network: A Comprehensive Foundation, Macmillan College Publishing Company (1994).
6. Min Qi, "Predicting US recessions with leading indicators via neural network models," International Journal of Forecasting, 17, 383-401 (2001).
7. Rumelhart, D. E., Hinton, G. E., Williams, R. J., "Learning internal representation by error propagation," in Rumelhart, D. E., McClelland, J. L., and the PDP research group (Eds), parallel distributed processing, MIT press, Cambridge, MA, 318-362 (1986).
8. Fogel, D. B., "An Information Criterion for Optimum Neural Network Selection," IEEE Transactions on Neural Networks, 2-5, 490-497 (1991).
9. Tugnait, J., "Fitting MA models to linear non Gaussian random field using higher order cumumants," IEEE Transactions on Signal Processing, 45, 1045-1050 (1997).
10. Perambur S. N., "Information-Theoretic Aspects of Neural Networks," CRC Press LLC, New York, USA (1999).