Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Hawraa Abbas ALMURIEB"'
Publikováno v:
Al-Bāhir, Vol 1, Iss 2 (2022)
Externí odkaz:
https://doaj.org/article/7d79b848f3a14d2cac2a4537ed0138ab
Publikováno v:
Al-Bāhir, Vol 1, Iss 1 (2022)
Externí odkaz:
https://doaj.org/article/da5f3f1a0a1c4258b9d0ef5615a5dc53
Publikováno v:
Journal of Interdisciplinary Mathematics. 24:2373-2379
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56bc724468d47e1ca97558853a9d288d
https://doi.org/10.1080/09720502.2021.1995193
https://doi.org/10.1080/09720502.2021.1995193
Publikováno v:
Journal of Interdisciplinary Mathematics. 24:1995-2004
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d905cf6e48ba81dba56380018ebe29a
https://doi.org/10.1080/09720502.2021.1964740
https://doi.org/10.1080/09720502.2021.1964740
Publikováno v:
Iraqi Journal of Science. :870-874
Some researchers are interested in using the flexible and applicable properties of quadratic functions as activation functions for FNNs. We study the essential approximation rate of any Lebesgue-integrable monotone function by a neural network of qua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::445108e342c82332755129865df63871
https://doi.org/10.24996/ijs.2020.61.4.20
https://doi.org/10.24996/ijs.2020.61.4.20
Publikováno v:
Full Text Book of Minar Congress.
Until today, many formulas of neural networks are defined to be used for function approximation, they vary with respect to the weights, activation functions and other standards. Moreover, researchers have studied the approximation of different spaces
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94e8b69553ea251f76f16f3e057e0778
https://doi.org/10.47832/minarcongress3-7
https://doi.org/10.47832/minarcongress3-7
Publikováno v:
Journal of Physics: Conference Series. 1804:012098
Quadratic functions give good rates of approximation when used as activation functions of feedforward neural networks. Also, monotonicity is important to describe the function behavior, so the behavior of its constrained approximation. Previously, th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a2d09c406cf76014e432372e190d2ff
https://doi.org/10.1088/1742-6596/1804/1/012098
https://doi.org/10.1088/1742-6596/1804/1/012098
Publikováno v:
Indonesian Journal of Electrical Engineering and Computer Science. 20:1584
For many years, approximation concepts has been investigated in view of neural networks for the several applications of the two topics. Researchers studied simultaneous approximation in the 2-normed space and proved essential theorems concern with ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1061df93ca57c407f488950968d5062d
https://doi.org/10.11591/ijeecs.v20.i3.pp1584-1590
https://doi.org/10.11591/ijeecs.v20.i3.pp1584-1590
Publikováno v:
IOP Conference Series: Materials Science and Engineering. 871:012040
Neural networks have a great place in approximating nonlinear functions, especially those Lebesgue integrable functions that are approximated by FNNs with one hidden layer and sigmoidal functions. Various operators of neural networks have been define
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d32035ac6dc7b0b960c4529919757459
https://doi.org/10.1088/1757-899x/871/1/012040
https://doi.org/10.1088/1757-899x/871/1/012040