Abstract
It is the aim of this contribution to continue our investigations on a special family of hyperbolic-type linear operators (here, for compactly supported continuous functions on IRn) which immediately can be interpreted as concrete real-time realizations of three-layer feedforward neural networks with sigma-pi units in the hidden layer. To indicate how these results are connected with density results we start with some introductory theorems on this topic. Moreover, we take a detailed look at the complexity of the generated neural networks in order to achieve global ε-accuracy.
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Lenze, B. Hyperbolic sigma-pi neural network operators for compactly supported continuous functions. Adv Comput Math 5, 163–172 (1996). https://doi.org/10.1007/BF02124741
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DOI: https://doi.org/10.1007/BF02124741