Improved RAN sequential prediction using orthogonal techniques

@article{Salmern2001ImprovedRS,
  title={Improved RAN sequential prediction using orthogonal techniques},
  author={Mois{\'e}s Salmer{\'o}n and Julio Ortega and Carlos Garc{\'i}a Puntonet and Alberto Prieto},
  journal={Neurocomputing},
  year={2001},
  volume={41},
  pages={153-172}
}
A new learning strategy for time-series prediction using radial basis function (RBF) networks is introduced. Its potential is examined in the particular case of the resource allocating network model, although the same ideas could apply to extend any other procedure. In the early stages of learning, addition of successive new groups of RBFs provides an increased rate of convergence. At the same time, the optimum lag structure is determined using orthogonal techniques such as QR factorization and… CONTINUE READING

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