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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/122786
Title: 
Introducing the Discriminative Paraconsistent Machine (DPM)
Author(s): 
Institution: 
Universidade Estadual Paulista (UNESP)
ISSN: 
0020-0255
Abstract: 
This paper introduces a new tool for pattern recognition. Called the Discriminative Paraconsistent Machine (DPM), it is based on a supervised discriminative model training that incorporates paraconsistency criteria and allows an intelligent treatment of contradictions and uncertainties. DPMs can be applied to solve problems in many fields of science, using the tests and discussions presented here, which demonstrate their efficacy and usefulness. Major difficulties and challenges that were overcome consisted basically in establishing the proper model with which to represent the concept of paraconsistency.
Issue Date: 
2013
Citation: 
Information Sciences, n. 221, p. 389-402, 2013.
Time Duration: 
389-402
Keywords: 
  • Paraconsistency
  • Pattern recognition
  • Discriminative model training
Source: 
http://dx.doi.org/10.1016/j.ins.2012.09.028
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/122786
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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