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Proceedings Paper

Nonlinear time series analysis with connectionist nets: toward a robust methodology
Author(s): Claas de Groot; Diethelm Wuertz
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Paper Abstract

We present a new methodology of time series analysis with connectionist networks. Our approach is based on a careful analysis of the appropriateness of `neural' concepts within the connectionist methodology. This methodology shows one serious drawback: lack of robustness. We conjecture that it is possible to overcome this difficulty by introducing a scheme that allows monitoring and interpretation of characteristic net values during the process of parameter estimation. We present the concept of time series analysis with connectionist networks and describe our new methodology in detail. In order to demonstrate the usefulness of this approach we present results for an artificial time series sampled form the `van der Pol equation.'

Paper Details

Date Published: 16 September 1992
PDF: 10 pages
Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.140068
Show Author Affiliations
Claas de Groot, Swiss Federal Institute of Technology (Switzerland)
Diethelm Wuertz, Swiss Federal Institute of Technology (Switzerland)


Published in SPIE Proceedings Vol. 1709:
Applications of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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