Nonlinear Dynamics Isolated by Delaunay Triangulation Criteria
2004 (English)In: Proceedings of the 43rd IEEE Conference on Decision and Control, 2004, 3862-3867 Vol.4 p.Conference paper (Refereed)
Inspired by an idea by Q. Zhang, we show that Delaunay triangulation of data points sampled from a system with an additive nonlinearity gives a criterion by which a linear projection can be found that isolates the nonlinear dependence, leaving out the linear one. This isolation means the nonlinear modeling can be confined to a regressor space of lower dimensionality, which in turn means over-parameterization can be avoided. Monte Carlo simulations indicate that a particular criterion built on triangle asymmetries has a minimum that coincides with the sampled system nonlinear part. The criterion is however complex to compute and non-convex, which makes it difficult to optimize globally.
Place, publisher, year, edition, pages
2004. 3862-3867 Vol.4 p.
Identification, Delaunay triangulation, Nonlinear modeling, Monte Carlo simulation
IdentifiersURN: urn:nbn:se:liu:diva-74813DOI: 10.1109/CDC.2004.1429340ISBN: 0-7803-8682-5OAI: oai:DiVA.org:liu-74813DiVA: diva2:495943
43rd IEEE Conference on Decision and Control, Paradise Island, Bahamas, December, 2004