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
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
收藏
页数:11
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