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Compactness of Neural Networks Cover
Open Access
|Dec 2022

Abstract

In this article, Feed-forward Neural Network is formalized in the Mizar system [1], [2]. First, the multilayer perceptron [6], [7], [8] is formalized using functional sequences. Next, we show that a set of functions generated by these neural networks satisfies equicontinuousness and equiboundedness property [10], [5]. At last, we formalized the compactness of the function set of these neural networks by using the Ascoli-Arzela’s theorem according to [4] and [3].

DOI: https://doi.org/10.2478/forma-2022-0002 | Journal eISSN: 1898-9934 | Journal ISSN: 1426-2630
Language: English
Page range: 13 - 21
Accepted on: Apr 30, 2022
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Published on: Dec 21, 2022
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2022 Keiichi Miyajima, Hiroshi Yamazaki, published by University of Białystok
This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 License.