Learning and Approximation Capabilities
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Lorenzo Vecci; Francesco Piazza; Aurelio Uncini
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Article
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1998
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Elsevier Science
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English
β 297 KB
In this paper, we study the theoretical properties of a new kind of artificial neural network, which is able to adapt its activation functions by varying the control points of a Catmull-Rom cubic spline. Most of all, we are interested in generalization capability, and we can show that our architectu