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      Un Algoritmo Recursivo de Reconocimiento de Patrones Translated title: A Recursive Pattern Recognition Algorithm

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          Abstract

          En este trabajo, proponemos un algoritmo de reconocimiento de patrones basado en el funcionamiento sistemático del neocórtex humano, en procesos de reconocimiento de patrones. El algoritmo explota la idea de recursividad, basada en la jerarquía neocortical y en la desagregación/integración del patrón en el proceso de reconocimiento. El algoritmo propuesto es probado para analizar sus capacidades de reconocimiento de patrones.

          Translated abstract

          This work presents a pattern recognition algorithm based on the systematic functioning of the human neocortex, in processes of pattern recognition. The algorithm exploits the idea of recursivity, based on the neocortical hierarchy and the decomposition/integration in the recognition process. The proposed algorithm is tested to analyze its capabilities of pattern recognition.

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          Most cited references12

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          Canonical computations of cerebral cortex.

          The idea that there is a fundamental cortical circuit that performs canonical computations remains compelling though far from proven. Here we review evidence for two canonical operations within sensory cortical areas: a feedforward computation of selectivity; and a recurrent computation of gain in which, given sufficiently strong external input, perhaps from multiple sources, intracortical input largely, but not completely, cancels this external input. This operation leads to many characteristic cortical nonlinearities in integrating multiple stimuli. The cortical computation must combine such local processing with hierarchical processing across areas. We point to important changes in moving from sensory cortex to motor and frontal cortex and the possibility of substantial differences between cortex in rodents vs. species with columnar organization of selectivity.
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            How does the brain keep information "in mind"?

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              Deep learning: Methods and applications

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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Journal
                rtfiuz
                Revista Técnica de la Facultad de Ingeniería Universidad del Zulia
                Rev. Téc. Ing. Univ. Zulia
                Facultad de Ingeniería, Universidad del Zulia (Maracaibo, Zulia, Venezuela )
                0254-0770
                August 2017
                : 40
                : 2
                : 095-104
                Affiliations
                [02] Mérida orgnameUniversidad de Los Andes orgdiv1Facultad de Ingeniería Venezuela aguilar@ 123456ula.ve
                [01] Cúcuta orgnameUniversidad Francisco de Paula Santander orgdiv1Facultad de Ingeniería Colombia eduardpuerto@ 123456ufps.edu.co
                Article
                S0254-07702017000200005
                9b85fcd8-28ac-4a72-9111-dba4f3d8c382

                http://creativecommons.org/licenses/by/4.0/

                History
                : 18 January 2016
                : 24 April 2017
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 12, Pages: 10
                Product

                SciELO Venezuela


                pattern recognition modules,recursividad,patrón,módulo de reconocimiento de patrones,recursivity,pattern

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