Abstract
We present a novel neural network method for extraction of the embedding function of a time series. We give results on two sets of computer-generated data which are known to show exponentially increasing divergence from nearby initial conditions. We use the network to predict the future evolution of these artificial mappings.
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References
G. Deco and D. Obradovic. An Information Theoretic Approach to Neural Computing. Springer, 1996.
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A. Weigend and N. Gershenfeld. Time Series Prediction, Forecasting the Future and Understanding the Past. Addison Wesley, 1996.
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© 1998 Springer-Verlag Wien
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Fyfe, C. (1998). An Unsupervised Neural Method for Time Series Analysis, Characterisation and Prediction. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_102
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DOI: https://doi.org/10.1007/978-3-7091-6492-1_102
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83087-1
Online ISBN: 978-3-7091-6492-1
eBook Packages: Springer Book Archive