Scholarlink

This paper builds upon the author’s recent research on the newly proposed Neural Network operators (Karsli, Const. Math. Anal., Proc. Book. July, 2023, 24–38) that employ wavelets. We present some asymptotic properties and quantitative findings related to these operators. The foundation of this study lies between the theories wavelet and approximation, along with knot points derived from the scaling functions of father wavelets. In subsequent sections, we will explore certain quantitative results and Voronovskaya-type theorems within various spaces.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Asymptotic and Quantitative Results of Neural Network Operators that Employ Wavelets

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Harun Karsli

摘要

This paper builds upon the author’s recent research on the newly proposed Neural Network operators (Karsli, Const. Math. Anal., Proc. Book. July, 2023, 24–38) that employ wavelets. We present some asymptotic properties and quantitative findings related to these operators. The foundation of this study lies between the theories wavelet and approximation, along with knot points derived from the scaling functions of father wavelets. In subsequent sections, we will explore certain quantitative results and Voronovskaya-type theorems within various spaces.