Neural Networks Art: Solving Problems with Multiple Solutions and New Teaching Algorithm
Dmitrienko V. D*, Yu. Zakovorotnyi A, Yu. Leonov S, Khavina I. P
Identifiers and Pagination:Year: 2014
First Page: 15
Last Page: 21
Publisher ID: TONEUJ-8-15
Article History:Received Date: 10/1/2014
Revision Received Date: 24/3/2014
Acceptance Date: 25/3/2014
Electronic publication date: 9 /9/2014
Collection year: 2014
open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
A new discrete neural networks adaptive resonance theory (ART), which allows solving problems with multiple solutions, is developed. New algorithms neural networks teaching ART to prevent degradation and reproduction classes at training noisy input data is developed. Proposed learning algorithms discrete ART networks, allowing obtaining different classification methods of input.