Nonlinear time series analysis with connectionist nets: toward a robust methodology
Claas de Groot, Diethelm Wuertz · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
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.'