PARSIMONIOUS DYNAMICAL RECONSTRUCTION

• ALISTAIR MEES

  Mathematics Department, The University of Western Australia, Nedlands, W. Australia 6009, Australia

抄録

Many nonlinear deterministic models of time series have large numbers of parameters and tend to overfit in the presence of noise. This paper shows how to generate radial basis function models with small numbers of parameters for a given quality of fit. It also addresses questions of how to select subsets from candidate sets of centers for radial basis function models, and what kinds of basis functions to use, as well as how large a model is appropriate.

収録刊行物

• International Journal of Bifurcation and Chaos

  International Journal of Bifurcation and Chaos 03 (03), 669-675, 1993-06

  World Scientific Pub Co Pte Lt

キーワード

• Applied Mathematics
• Modeling and Simulation
• Engineering (miscellaneous)

詳細情報

• CRID: 1362825893997676544
• NII論文ID: 30010730887
• DOI: 10.1142/s021812749300057x
• ISSN: 17936551
• ISSN: 02181274
• Web Site: https://www.worldscientific.com/doi/pdf/10.1142/S021812749300057X
• データソース種別:
  • Crossref
  • CiNii Articles