Adaptive Pointing Theory (APT) Artificial Neural Network

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.

Description

Title: Adaptive Pointing Theory (APT) Artificial Neural Network
Author/s:
  • Al-Rawi, Kamal
  • Gonzalo Martín, Consuelo
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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Abstract

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.

More information

Item ID: 35627
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
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