A node pruning algorithm based on a Fourier amplitude sensitivity test method

@article{Lauret2006ANP,
  title={A node pruning algorithm based on a Fourier amplitude sensitivity test method},
  author={Alfred Jean Philippe Lauret and Eric Fock and Thierry Alex Mara},
  journal={IEEE Transactions on Neural Networks},
  year={2006},
  volume={17},
  pages={273-293}
}
In this paper, we propose a new pruning algorithm to obtain the optimal number of hidden units of a single layer of a fully connected neural network (NN). The technique relies on a global sensitivity analysis of model output. The relevance of the hidden nodes is determined by analysing the Fourier decomposition of the variance of the model output. Each hidden unit is assigned a ratio (the fraction of variance which the unit accounts for) that gives their ranking. This quantitative information… CONTINUE READING
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