Universal Approximation Using Shuffled Linear Models

@inproceedings{Bliek2013UniversalAU,
  title={Universal Approximation Using Shuffled Linear Models},
  author={Laurens Bliek},
  year={2013}
}
This paper proposes a specific type of Local Linear Model, the Shuffled Linear Model (SLM), that can be used as a universal approximator. Local operating points are chosen randomly and linear models are used to approximate a function or system around these points. The model can also be interpreted as an extension to Extreme Learning Machines with Radial Basis Function nodes, or as a specific way of using Takagi-Sugeno fuzzy models. Using the available theory of Extreme Learning Machines… CONTINUE READING
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C

  • F. Fernández-Navarro
  • Hervás-Mart́ınez, J. Sanchez-Monedero, P. A. Guti…
  • 2011
1 Excerpt

Non linear system identification: a state-space approach

  • V. Verdult
  • Twente University Press
  • 2002
1 Excerpt

Nonlinear system identification: from classical approaches to neural networks and fuzzy models

  • O. Nelles
  • Springer
  • 2001
1 Excerpt

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