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Abstract: We present a time-series predicton method based on the combination of an unsupervised growing neural network -- Dynamic Cell Structures (DCS) and local linear models (LLMs). DCS is used for representation of the attractor of the underlying dynamical system in the form of directed graph and thus provides the proper quantization of the state space data. Whereas such a model provides a highly accurate prediction of "simple" data (e.g. Mackey-Glass chaotic data), for data which exhibits so called... (Update)
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BibTeX entry: (Update)
Chudy, L., & Farkas, I. (1998). Prediction of chaotic time-series using dynamic cell structuresand local linear models. Neural Network World, 8 (5), 481-489. http://citeseer.ist.psu.edu/chudy98prediction.html More
@misc{ chudy98prediction,
author = "L. Chudy and I. Farkas",
title = "Prediction of chaotic time-series using dynamic cell structuresand local
linear models",
text = "Chudy, L., & Farkas, I. (1998). Prediction of chaotic time-series using
dynamic cell structuresand local linear models. Neural Network World, 8
(5), 481-489.",
year = "1998",
url = "citeseer.ist.psu.edu/chudy98prediction.html" }
Citations (may not include all citations):1213 Self-Organizing Maps (context) - Kohonen - 1997
283 Some methods for classification and analysis of multivariate.. - MacQueen - 1967
169 Growing cell structures - a self-organizing network for unsu.. - Fritzke - 1994
168 Time Series Prediction: Forecasting the Future and Understan.. (context) - Weigend, Gershenfeld - 1994
127 Oscillations and chaos in physiological control systems (context) - Mackey, Glass - 1977
116 A growing neural gas network learns topologies - Fritzke - 1995
96 Predicting chaotic time series (context) - Farmer, Sidorowich - 1987
95 Nonlinear signal processing using neural networks: Predictio.. (context) - Lapedes, Farber - 1987
93 Topology representing networks (context) - Martinetz - 1994
92 A resource-allocating network for function interpolation (context) - Platt - 1991
70 Neural-gas network for vector quantization and its applicati.. (context) - Martinetz, Berkovich et al. - 1993
46 IEEE Transactions on Information Theory (context) - Lloyd, quantization - 1982
31 Time series prediction by using a connectionist network with.. (context) - Wan - 1994
31 Incremental grid growing: encoding high-dimensional structur.. - Blackmore, Miikkulainen - 1993
28 Dynamic cell structure learns perfectly topology preserving .. (context) - Bruske, Sommer - 1995
[Article contains additional citations not shown here]
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