1 March 1998 Study of the approximation capabilities of two four-layered neural networks
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Abstract
The approximation capabilities of two different four-layered neural networks are studied. First, a network with the backpropagation algorithm is analyzed, and its error surface, convergence properties, and network design are considered. An alternative to the backpropagation approach is presented, namely, we construct a network that uses a one- pass algorithm. We show that the proposed network can correctly classify N different patterns with 4 ?N?3 hidden units. We also show that an arbitrarily small approximation error can be obtained for this network by adjusting the appropriate parameters.
Claudia Mello-Thoms, Stanley M. Dunn, "Study of the approximation capabilities of two four-layered neural networks," Optical Engineering 37(3), (1 March 1998). https://doi.org/10.1117/1.601923
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