When is approximation by Gaussian networks necessarily a linear process?

@article{Mhaskar2004WhenIA,
  title={When is approximation by Gaussian networks necessarily a linear process?},
  author={Hrushikesh Narhar Mhaskar},
  journal={Neural networks : the official journal of the International Neural Network Society},
  year={2004},
  volume={17 7},
  pages={
          989-1001
        }
}
Let s > or = 1 be an integer. A Gaussian network is a function on Rs of the form [Formula: see text]. The minimal separation among the centers, defined by (1/2) min(1 < or = j not = k < or = N) [Formula: see text], is an important characteristic of the network that determines the stability of interpolation by Gaussian networks, the degree of approximation by such networks, etc. Let (within this abstract only) the set of all Gaussian networks with minimal separation exceeding 1/m be denoted by… CONTINUE READING

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