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Nonparametric regression estimation by normalized radial basis function networks

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2 Author(s)
Devroye, L. ; Dept. of Comput. Sci. & Software Eng., Concordia Univ., Montreal, Que., Canada ; Schafer, D.

This paper establishes weak and strong universal consistency of regression estimates based on normalized radial basis function networks when the network parameters are chosen by empirical risk minimization.

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Information Theory, IEEE Transactions on  (Volume:51 ,  Issue: 3 )