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Additional perspectives on feedforward neural-nets and the functional-link

By: Yoh-Han Pao; Igelnik, B.;

1993 / IEEE / 0-7803-1421-2

Description

This item was taken from the IEEE Periodical ' Additional perspectives on feedforward neural-nets and the functional-link ' It has been proved that multilayer feedforward neural-nets with as few as a single hidden layer can serve as universal approximators of functions mapping multidimensional space R/sup s/ to one-dimensional space R. Our prior experience has provided us with ample pragmatic evidence that the model can be simplified, with use of functional-links which need not be learned. In this paper, we prove theorems which provide a theoretical justification for use of the highly efficient functional-link approach.