NDLI: Stechkin-Marchaud Inequality in Terms of Neural Networks Approximation in Lp- Space for 0 <p <1

Content Provider	Scilit
Author	Bhaya, Eman Samir Al-Sadaa, Zaineb Hussain Abd
Copyright Year	2019
Description	Journal: Iop Conference Series: Materials Science and Engineering The approximation by neural networks is growing field, it attracts many mathematics, computer, sciences and economic researchers. In the recent years some researchers studied Stechkin-Marchaud type inequalities of Bernstem-Darmeyer operator. In this article we give Stechkin-Marchaud type theorem for an operator we defined it. As a direct consequence we prove a lower bound result for neural networks with ω$ _{ k }$ $(f_{i}$ $δ)_{ p }$.
Related Links	https://iopscience.iop.org/article/10.1088/1757-899X/571/1/012020/pdf
ISSN	17578981
e-ISSN	1757899X
DOI	10.1088/1757-899x/571/1/012020
Journal	Iop Conference Series: Materials Science and Engineering
Issue Number	1
Volume Number	571
Language	English
Publisher	IOP Publishing
Publisher Date	2019-07-01
Access Restriction	Open
Subject Keyword	Journal: Iop Conference Series: Materials Science and Engineering Cybernetical Science Stechkin Marchaud
Content Type	Text
Resource Type	Article

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