Johannes Schmidt-Hieber, “The Kolmogorov–Arnold representation theorem revisited”, Neural Networks, 137, 2021, 119
Eduardo Paluzo-Hidalgo, Rocio Gonzalez-Diaz, Miguel A. Gutiérrez-Naranjo, Jónathan Heras, “Simplicial-Map Neural Networks Robust to Adversarial Examples”, Mathematics, 9, № 2, 2021, 169
Ming-Xi Wang, Yang Qu, “Approximation capabilities of neural networks on unbounded domains”, Neural Networks, 145, 2022, 56
Ji Han, Shou-Ming Hou, 11507, Advances in Computational Intelligence, 2019, 87
Tim De Ryck, Samuel Lanthaler, Siddhartha Mishra, “On the approximation of functions by tanh neural networks”, Neural Networks, 143, 2021, 732
Christian Beck, Arnulf Jentzen, Benno Kuckuck, “Full error analysis for the training of deep neural networks”, Infin. Dimens. Anal. Quantum. Probab. Relat. Top., 25, № 02, 2022, 2150020
Sri Kusumadewi, Linda Rosita, Elyza Gustri Wahyuni, “Implementation of fuzzy associative memory toward optimizing a neural network model to predict total iron binding capacity”, Biomedical Signal Processing and Control, 86, 2023, 105297
Y.B. Yu, W.B. Ni, K. Xuan, W.M. Li, W. Xu, C. Li, G.F. Liu, “Neural network structure optimization for Hefei Light Source II β function correction”, J. Inst., 18, № 09, 2023, P09008
Danilo Costarelli, Anna Rita Sambucini, Gianluca Vinti, “Convergence in Orlicz spaces by means of the multivariate max-product neural network operators of the Kantorovich type and applications”, Neural Comput & Applic, 31, № 9, 2019, 5069
Rujira Jullapak, Tongjai Yampaka, 2021 18th International Joint Conference on Computer Science and Software Engineering (JCSSE), 2021, 1