Structured neural network modelling of multi-valued functions for wind vector retrieval from satellite scatterometer measurements

@article{Evans2000StructuredNN,
  title={Structured neural network modelling of multi-valued functions for wind vector retrieval from satellite scatterometer measurements},
  author={David J. Evans and Dan Cornford and Ian T. Nabney},
  journal={Neurocomputing},
  year={2000},
  volume={30},
  pages={23-30}
}
A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article Mixture Density Networks, a principled method for modelling conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid Mixture Density Network… CONTINUE READING