Year: 2023
Author: Dansheng Yu, Yunyou Qian, Fengjun Li
Analysis in Theory and Applications, Vol. 39 (2023), Iss. 1 : pp. 93–104
Abstract
Recently, Li [16] introduced three kinds of single-hidden layer feed-forward neural networks with optimized piecewise linear activation functions and fixed weights, and obtained the upper and lower bound estimations on the approximation accuracy of the FNNs, for continuous function defined on bounded intervals. In the present paper, we point out that there are some errors both in the definitions of the FNNs and in the proof of the upper estimations in [16]. By using new methods, we also give right approximation rate estimations of the approximation by Li’s neural networks.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/ata.OA-2021-0006
Analysis in Theory and Applications, Vol. 39 (2023), Iss. 1 : pp. 93–104
Published online: 2023-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 12
Keywords: Approximation rate modulus of continuity modulus of smoothness neural network operators.
Author Details
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Construction and approximation rate for feedforward neural network operators with sigmoidal functions
Yu, Dansheng
Cao, Feilong
Journal of Computational and Applied Mathematics, Vol. 453 (2025), Iss. P.116150
https://doi.org/10.1016/j.cam.2024.116150 [Citations: 4]