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International Journal of Innovation and Applied Studies
ISSN: 2028-9324     CODEN: IJIABO     OCLC Number: 828807274     ZDB-ID: 2703985-7
 
 
Thursday 17 June 2021

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  Call for Papers - August 2021     |     Now IJIAS is indexed in EBSCO, ResearchGate, ProQuest, Chemical Abstracts Service, Index Copernicus, IET Inspec Direct, Ulrichs Web, Google Scholar, CAS Abstracts, J-Gate, UDL Library, CiteSeerX, WorldCat, Scirus, Research Bible and getCited, etc.  
 
 
 

Neurocomputing in pattern recognition


[ Neurocomputing en el reconocimiento de patrones ]

Volume 32, Issue 4, May 2021, Pages 449–456

 Neurocomputing in pattern recognition

Jorge Hidalgo Larrea1, Mitchell Vásquez Bermúdez2, María Avilés Vera3, and José Salavarría Melo4

1 Carrera de Computación e Informática, Universidad Agraria del Ecuador, Guayaquil, Guayas, Ecuador
2 Carrera de Computación e Informática, Universidad Agraria del Ecuador, Guayaquil, Guayas, Ecuador
3 Carrera de Computación e Informática, Universidad Agraria del Ecuador, Guayaquil, Guayas, Ecuador
4 Carrera de Computación e Informática, Universidad Agraria del Ecuador, Guayaquil, Guayas, Ecuador

Original language: Spanish

Copyright © 2021 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


In this work, a bibliographic review on neurocomputing and the role it plays in pattern recognition has been carried out, the algorithms proposed by different authors have been studied and a report has been made of the most relevant works that apply the technique of pattern recognition. This study has been carried out due to the importance that the use of neurocomputing currently has for information processing in some areas such as sensor processing, data analysis and analysis of control aspects and in general where there is no algorithm that provides a solution. The methodology used allowed identifying, evaluating and analyzing various related studies to later apply a systematic categorization model and obtain the characteristics with their respective descriptions. In this way many algorithms that seek to solve the pattern recognition problem are based in computing models that imitate the way the human brain work focused on high-level cognitive functions such as neural networks characterized by their ability to generalize the information that implies learning processes or architectures under deep learning, however the trend that advances significantly involves the extraction of characteristics in the recognition of emotions.

Author Keywords: Neurocomputing, neural network, categorization, descriptors, architecture, model, pattern.


How to Cite this Article


Jorge Hidalgo Larrea, Mitchell Vásquez Bermúdez, María Avilés Vera, and José Salavarría Melo, “Neurocomputing in pattern recognition,” International Journal of Innovation and Applied Studies, vol. 32, no. 4, pp. 449–456, May 2021.