Stechkin-Marchaud Inequality in Terms of Neural Networks Approximation in Lp - Space for 0

2nd International Scientific Conference (Pure Sciences, Brilliant Creativity and Renewed Building)

Bhaya, Eman Samir^1 ; Abd Al-Sadaa, Zaineb Hussain^1

University of Babylon, College of Education for Pure Sciences, Mathematics Department, Iraq^1

关键词: Approximation;    inverse theorem;    L-p spaces;    Lower bounds;    Stechkin-Marchaud inequality;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/571/1/012020/pdf
DOI  :  10.1088/1757-899X/571/1/012020

来源: IOP

【 摘 要 】

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 (fi δ)p.