A Jackson-type estimate in terms of the \(\tau\)-modulus for neural network operators in \(L^{p}\)-spaces

In this paper, we study the order of approximation with respect to the \(L^{p}\)-norm for the (shallow) neural network (NN) operators. We establish a Jackson-type estimate for the considered family of discrete approximation operators using the averaged modulus of smoothness introduced by Sendov and...

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Bibliographic Details
Main Authors: Lorenzo Boccali, Danilo Costarelli, Gianluca Vinti
Format: Article
Language:English
Published: Tuncer Acar 2024-08-01
Series:Modern Mathematical Methods
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Online Access:https://modernmathmeth.com/index.php/pub/article/view/42
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