Abstract
This paper deals with the problem of the discrimination between well-predictable and not-well-predictable time series. One criterion for the separation is given by the size of the Lyapunov exponent, which was originally defined for deterministic systems. However, the Lyapunov exponent can also be analyzed and used for stochastic time series. Experimental results illustrate the classification between well-predictable and not-well-predictable time series.
This work has been supported by the Deutsche Forschungsgemeinschaft, Sonderforschungsbereich 475.
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Busse, A.M. (2005). Classification of Processes by the Lyapunov Exponent. In: Weihs, C., Gaul, W. (eds) Classification — the Ubiquitous Challenge. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28084-7_75
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DOI: https://doi.org/10.1007/3-540-28084-7_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25677-9
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