Some density results by deep Kantorovich type neural network operators

被引：6

作者：

Sharma, Manju ^{[1
]}

Singh, Uaday ^{[1
]}

机构：

[1] Indian Inst Technol Roorkee, Dept Math, Roorkee 247667, Uttarakhand, India

来源：

JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS | 2024年 / 533卷 / 02期

关键词：

Neural networks; Deep neural network operators; Approximation; Density results; APPROXIMATION; CONVERGENCE;

D O I：

10.1016/j.jmaa.2023.128009

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we prove density results by using deep Kantorovich type neural network operators. Firstly, we define a two layer neural network operator and prove the density results in the spaces C(I) and Lp(I) for p >= 1, where I := [-1, 1]. Then we extend it to a multi-layer neural network operator and prove the corresponding density results. Our study provides a generalizations of the well known single layer Kantorovich type neural network operator in terms of its deeper version.(c) 2023 Elsevier Inc. All rights reserved.

引用

页数：11

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