Abstract
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 ωk (fi δ)p.
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More From: IOP Conference Series: Materials Science and Engineering
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