Please use this identifier to cite or link to this item: http://dspace.utpl.edu.ec/handle/123456789/18706
Title: Learning Algorithm for the Recursive Pattern Recognition Model
Authors: Aguilar Castro, J.
Keywords: Engineering controlled terms: Character recognition
Pattern recognition Engineering main heading: Learning algorithms
metadata.dc.date.available: 2017-06-16T22:02:14Z
Issue Date: 8-Aug-2016
Publisher: Applied Artificial Intelligence
Abstract: In this work, we incorporate a learning algorithm to the recursive pattern recognition model, based on the systematic functioning of the human neocortex presented in previous works. This algorithm has two mechanisms: the first, called Aprendizaje_nuevo, is used to learn new patterns and creates a new pattern recognition module in the model. The other, called Aprendizaje_por_refuerzo, is used to reinforce a pattern and adapts the module that represents the pattern to the changes in it. The algorithm is tested in various contexts (text and images) to analyze its capacities of learning and of recognition of the model. © 2016 Taylor & Francis.
metadata.dc.identifier.other: 10.1080/08839514.2016.1213584
URI: http://dspace.utpl.edu.ec/handle/123456789/18706
ISBN: 8839514
Other Identifiers: 10.1080/08839514.2016.1213584
Other Identifiers: 10.1080/08839514.2016.1213584
metadata.dc.language: Inglés
metadata.dc.type: Article
Appears in Collections:Artículos de revistas Científicas

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