Probability Density Function Learning by Unsupervised Neurons

@article{Fiori2001ProbabilityDF,
  title={Probability Density Function Learning by Unsupervised Neurons},
  author={Simone G. O. Fiori},
  journal={International journal of neural systems},
  year={2001},
  volume={11 5},
  pages={
          399-417
        }
}
In a recent work, we introduced the concept of pseudo-polynomial adaptive activation function neuron (FAN) and presented an unsupervised information-theoretic learning theory for such structure. The learning model is based on entropy optimization and provides a way of learning probability distributions from incomplete data. The aim of the present paper is to illustrate some theoretical features of the FAN neuron, to extend its learning theory to asymmetrical density function approximation, and… CONTINUE READING

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