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Al-Rawi, Kamal and Gonzalo Martín, Consuelo (2014). Adaptive Pointing Theory (APT) Artificial Neural Network. "International Journal of Computer and Communication Engineering", v. 3 (n. 3); pp. 212-215. ISSN 2010-3743. https://doi.org/10.7763/IJCCE.2014.V3.322.
Title: | Adaptive Pointing Theory (APT) Artificial Neural Network |
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Author/s: |
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Item Type: | Article |
Título de Revista/Publicación: | International Journal of Computer and Communication Engineering |
Date: | May 2014 |
ISSN: | 2010-3743 |
Volume: | 3 |
Subjects: | |
Freetext Keywords: | Adaptive pointing theory; APT ANN; Adaptive resonance theory; ART ANN; ARTMAP; compact fuzzy ART; artificial neural networks |
Faculty: | E.T.S. de Ingenieros Informáticos (UPM) |
Department: | Arquitectura y Tecnología de Sistemas Informáticos |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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The choice value and the testing process against the vigilance parameter, characteristic of ART Neural Network, are merged. Only, a single unique test is required to determine if a committed category node can represent the current input or not. Advantages of APT over ART are: 1-Avoid testing every committed category node before deciding to train a committed category node or a new node must be committed, 2-The vigilance parameter is fixed during training, and 3-The choice value parameter is eliminated.
Item ID: | 35627 |
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DC Identifier: | http://oa.upm.es/35627/ |
OAI Identifier: | oai:oa.upm.es:35627 |
DOI: | 10.7763/IJCCE.2014.V3.322 |
Official URL: | http://www.ijcce.org/ |
Deposited by: | Memoria Investigacion |
Deposited on: | 08 Jul 2015 12:10 |
Last Modified: | 17 Nov 2017 08:54 |