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  • Source: Neurocomputing. Conference titles: Brazilian Symposium on Neural Networks - SBRN. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      LIANG, Xiaoming e LIANG, Zhao. Effect of nonidentical signal phases on signal amplification of two coupled excitable neurons. Neurocomputing. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.neucom.2013.06.041. Acesso em: 17 ago. 2024. , 2014
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      Liang, X., & Liang, Z. (2014). Effect of nonidentical signal phases on signal amplification of two coupled excitable neurons. Neurocomputing. Amsterdam: Elsevier. doi:10.1016/j.neucom.2013.06.041
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      Liang X, Liang Z. Effect of nonidentical signal phases on signal amplification of two coupled excitable neurons [Internet]. Neurocomputing. 2014 ; 127 21-29.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2013.06.041
    • Vancouver

      Liang X, Liang Z. Effect of nonidentical signal phases on signal amplification of two coupled excitable neurons [Internet]. Neurocomputing. 2014 ; 127 21-29.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2013.06.041
  • Source: Neurocomputing. Conference titles: Brazilian Symposium on Neural Networks - SBRN. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      CUPERTINO, Thiago H e GUELERI, Roberto e LIANG, Zhao. A semi-supervised classification technique based on interacting forces. Neurocomputing. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.neucom.2013.05.050. Acesso em: 17 ago. 2024. , 2014
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      Cupertino, T. H., Gueleri, R., & Liang, Z. (2014). A semi-supervised classification technique based on interacting forces. Neurocomputing. Amsterdam: Elsevier. doi:10.1016/j.neucom.2013.05.050
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      Cupertino TH, Gueleri R, Liang Z. A semi-supervised classification technique based on interacting forces [Internet]. Neurocomputing. 2014 ; 127 43-51.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2013.05.050
    • Vancouver

      Cupertino TH, Gueleri R, Liang Z. A semi-supervised classification technique based on interacting forces [Internet]. Neurocomputing. 2014 ; 127 43-51.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2013.05.050
  • Source: Neurocomputing. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      CUPERTINO, Thiago H e HUERTAS, Jean e LIANG, Zhao. Data clustering using controlled consensus in complex networks. Neurocomputing, v. 118, p. 132-140, 2013Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2013.02.026. Acesso em: 17 ago. 2024.
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      Cupertino, T. H., Huertas, J., & Liang, Z. (2013). Data clustering using controlled consensus in complex networks. Neurocomputing, 118, 132-140. doi:10.1016/j.neucom.2013.02.026
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      Cupertino TH, Huertas J, Liang Z. Data clustering using controlled consensus in complex networks [Internet]. Neurocomputing. 2013 ; 118 132-140.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2013.02.026
    • Vancouver

      Cupertino TH, Huertas J, Liang Z. Data clustering using controlled consensus in complex networks [Internet]. Neurocomputing. 2013 ; 118 132-140.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2013.02.026
  • Source: Neurocomputing. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      SILVA, Thiago C e LIANG, Zhao. Semi-supervised learning guided by the modularity measure in complex networks. Neurocomputing, v. fe 2012, n. 1, p. 30-37, 2012Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2011.04.042. Acesso em: 17 ago. 2024.
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      Silva, T. C., & Liang, Z. (2012). Semi-supervised learning guided by the modularity measure in complex networks. Neurocomputing, fe 2012( 1), 30-37. doi:10.1016/j.neucom.2011.04.042
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      Silva TC, Liang Z. Semi-supervised learning guided by the modularity measure in complex networks [Internet]. Neurocomputing. 2012 ; fe 2012( 1): 30-37.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2011.04.042
    • Vancouver

      Silva TC, Liang Z. Semi-supervised learning guided by the modularity measure in complex networks [Internet]. Neurocomputing. 2012 ; fe 2012( 1): 30-37.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2011.04.042
  • Source: Neural Networks. Unidade: ICMC

    Assunto: REDES NEURAIS

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      BREVE, Fabricio A. et al. Chaotic phase synchronization and desynchronization in an oscillator network for object selection. Neural Networks, v. 22, n. 5-6, p. 728-737, 2009Tradução . . Disponível em: https://doi.org/10.1016/j.neunet.2009.06.027. Acesso em: 17 ago. 2024.
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      Breve, F. A., Zhao, L., Quiles, M. G., & Macau, E. E. N. (2009). Chaotic phase synchronization and desynchronization in an oscillator network for object selection. Neural Networks, 22( 5-6), 728-737. doi:10.1016/j.neunet.2009.06.027
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      Breve FA, Zhao L, Quiles MG, Macau EEN. Chaotic phase synchronization and desynchronization in an oscillator network for object selection [Internet]. Neural Networks. 2009 ;22( 5-6): 728-737.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neunet.2009.06.027
    • Vancouver

      Breve FA, Zhao L, Quiles MG, Macau EEN. Chaotic phase synchronization and desynchronization in an oscillator network for object selection [Internet]. Neural Networks. 2009 ;22( 5-6): 728-737.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neunet.2009.06.027
  • Source: Neurocomputing. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      QUILES, Marcos Gonçalves et al. A network of integrate and fire neurons for visual selection. Neurocomputing, v. 72, n. 10-12, p. 2198-2208, 2009Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2008.10.024. Acesso em: 17 ago. 2024.
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      Quiles, M. G., Liang Zhao,, Breve, F. A., & Romero, R. A. F. (2009). A network of integrate and fire neurons for visual selection. Neurocomputing, 72( 10-12), 2198-2208. doi:10.1016/j.neucom.2008.10.024
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      Quiles MG, Liang Zhao, Breve FA, Romero RAF. A network of integrate and fire neurons for visual selection [Internet]. Neurocomputing. 2009 ; 72( 10-12): 2198-2208.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2008.10.024
    • Vancouver

      Quiles MG, Liang Zhao, Breve FA, Romero RAF. A network of integrate and fire neurons for visual selection [Internet]. Neurocomputing. 2009 ; 72( 10-12): 2198-2208.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2008.10.024
  • Source: Neurocomputing. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      DELBEM, Alexandre Cláudio Botazzo e CORRÊA, Leonardo Garcia e ZHAO, Liang. Design of associative memories using cellular neural networks. Neurocomputing, v. 72, n. 10-12, p. 2180-2188, 2009Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2008.06.029. Acesso em: 17 ago. 2024.
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      Delbem, A. C. B., Corrêa, L. G., & Zhao, L. (2009). Design of associative memories using cellular neural networks. Neurocomputing, 72( 10-12), 2180-2188. doi:10.1016/j.neucom.2008.06.029
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      Delbem ACB, Corrêa LG, Zhao L. Design of associative memories using cellular neural networks [Internet]. Neurocomputing. 2009 ; 72( 10-12): 2180-2188.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2008.06.029
    • Vancouver

      Delbem ACB, Corrêa LG, Zhao L. Design of associative memories using cellular neural networks [Internet]. Neurocomputing. 2009 ; 72( 10-12): 2180-2188.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2008.06.029
  • Source: Neurocomputing. Unidades: EACH, ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      OLIVEIRA, Patrícia Rufino e ROMERO, Roseli Aparecida Francelin. Improvements on ICA mixture models for image pre-processing and segmentation. Neurocomputing, v. 71, n. 10-12, p. 2180-2193, 2008Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2007.10.016. Acesso em: 17 ago. 2024.
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      Oliveira, P. R., & Romero, R. A. F. (2008). Improvements on ICA mixture models for image pre-processing and segmentation. Neurocomputing, 71( 10-12), 2180-2193. doi:10.1016/j.neucom.2007.10.016
    • NLM

      Oliveira PR, Romero RAF. Improvements on ICA mixture models for image pre-processing and segmentation [Internet]. Neurocomputing. 2008 ; 71( 10-12): 2180-2193.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2007.10.016
    • Vancouver

      Oliveira PR, Romero RAF. Improvements on ICA mixture models for image pre-processing and segmentation [Internet]. Neurocomputing. 2008 ; 71( 10-12): 2180-2193.[citado 2024 ago. 17 ] Available from: https://doi.org/10.1016/j.neucom.2007.10.016

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