Filtros : "Indexado no Current Contents" "LIANG, ZHAO" Removidos: "Santos, Regina Helena de Almeida" "ITO, AMANDO SIUITI" "FMRP" Limpar

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  • Source: Physical Review E. Unidade: FFCLRP

    Subjects: AMPLIFICADORES ÓPTICOS, SISTEMAS NÃO LINEARES, TOPOLOGIA EM COMPUTAÇÃO

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      LIANG, Xiaoming et al. Amplified signal response by cluster synchronization competition in rings with short-distance couplings. Physical Review E, v. 106, n. 6, 2022Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.106.064306. Acesso em: 19 ago. 2024.
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      Liang, X., Hua, L., Zhang, X., & Liang, Z. (2022). Amplified signal response by cluster synchronization competition in rings with short-distance couplings. Physical Review E, 106( 6). doi:10.1103/PhysRevE.106.064306
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      Liang X, Hua L, Zhang X, Liang Z. Amplified signal response by cluster synchronization competition in rings with short-distance couplings [Internet]. Physical Review E. 2022 ; 106( 6):[citado 2024 ago. 19 ] Available from: https://doi.org/10.1103/PhysRevE.106.064306
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      Liang X, Hua L, Zhang X, Liang Z. Amplified signal response by cluster synchronization competition in rings with short-distance couplings [Internet]. Physical Review E. 2022 ; 106( 6):[citado 2024 ago. 19 ] Available from: https://doi.org/10.1103/PhysRevE.106.064306
  • Source: Nature Communications. Unidade: FFCLRP

    Subjects: VALORES ATÍPICOS, ANÁLISE MULTIVARIADA, ANÁLISE DE SÉRIES TEMPORAIS

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      FERREIRA, Leonardo N. et al. Spatiotemporal data analysis with chronological networks. Nature Communications, v. 11, 2020Tradução . . Disponível em: https://doi.org/10.1038/s41467-020-17634-2. Acesso em: 19 ago. 2024.
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      Ferreira, L. N., Vega-Oliveros, D. A., Cotacallapa, M., Cardoso, M. F., Quiles, M. G., Macau, E. E. N., & Liang, Z. (2020). Spatiotemporal data analysis with chronological networks. Nature Communications, 11. doi:10.1038/s41467-020-17634-2
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      Ferreira LN, Vega-Oliveros DA, Cotacallapa M, Cardoso MF, Quiles MG, Macau EEN, Liang Z. Spatiotemporal data analysis with chronological networks [Internet]. Nature Communications. 2020 ; 11[citado 2024 ago. 19 ] Available from: https://doi.org/10.1038/s41467-020-17634-2
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      Ferreira LN, Vega-Oliveros DA, Cotacallapa M, Cardoso MF, Quiles MG, Macau EEN, Liang Z. Spatiotemporal data analysis with chronological networks [Internet]. Nature Communications. 2020 ; 11[citado 2024 ago. 19 ] Available from: https://doi.org/10.1038/s41467-020-17634-2
  • Source: Neural Networks. Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, OTIMIZAÇÃO MATEMÁTICA

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      CARNEIRO, Murillo G. et al. Particle swarm optimization for network-based data classification. Neural Networks, v. 110, p. 243-255, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.neunet.2018.12.003. Acesso em: 19 ago. 2024.
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      Carneiro, M. G., Cheng, R., Zhao, L., & Jin, Y. (2019). Particle swarm optimization for network-based data classification. Neural Networks, 110, 243-255. doi:10.1016/j.neunet.2018.12.003
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      Carneiro MG, Cheng R, Zhao L, Jin Y. Particle swarm optimization for network-based data classification [Internet]. Neural Networks. 2019 ; 110 243-255.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.neunet.2018.12.003
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      Carneiro MG, Cheng R, Zhao L, Jin Y. Particle swarm optimization for network-based data classification [Internet]. Neural Networks. 2019 ; 110 243-255.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.neunet.2018.12.003
  • Source: Information Sciences. Unidade: FFCLRP

    Subjects: RECONHECIMENTO DE PADRÕES, MÚSICA

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      COCA, Andrés E e LIANG, Zhao. Musical rhythmic pattern extraction using relevance of communities in networks. Information Sciences, v. 329, p. 819-848, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2015.09.030. Acesso em: 19 ago. 2024.
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      Coca, A. E., & Liang, Z. (2016). Musical rhythmic pattern extraction using relevance of communities in networks. Information Sciences, 329, 819-848. doi:10.1016/j.ins.2015.09.030
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      Coca AE, Liang Z. Musical rhythmic pattern extraction using relevance of communities in networks [Internet]. Information Sciences. 2016 ; 329 819-848.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.ins.2015.09.030
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      Coca AE, Liang Z. Musical rhythmic pattern extraction using relevance of communities in networks [Internet]. Information Sciences. 2016 ; 329 819-848.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.ins.2015.09.030
  • Source: Information Sciences. Unidade: FFCLRP

    Subjects: RECONHECIMENTO DE PADRÕES, REDES COMPLEXAS, ALGORITMOS

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      FERREIRA, Leonardo N. Time series clustering via community detection in networks. Information Sciences, v. 326, p. 227-242, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2015.07.046. Acesso em: 19 ago. 2024.
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      Ferreira, L. N. (2016). Time series clustering via community detection in networks. Information Sciences, 326, 227-242. doi:10.1016/j.ins.2015.07.046
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      Ferreira LN. Time series clustering via community detection in networks [Internet]. Information Sciences. 2016 ; 326 227-242.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.ins.2015.07.046
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      Ferreira LN. Time series clustering via community detection in networks [Internet]. Information Sciences. 2016 ; 326 227-242.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.ins.2015.07.046
  • Source: Neurocomputing. Unidades: FFCLRP, ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, RECONHECIMENTO DE OBJETOS

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      BENICASA, Alcides X et al. An object-based visual selection framework. Neurocomputing, v. 180, p. 35-54, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2015.10.111. Acesso em: 19 ago. 2024.
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      Benicasa, A. X., Quiles, M. G., Silva, T. C., Liang, Z., & Romero, R. A. F. (2016). An object-based visual selection framework. Neurocomputing, 180, 35-54. doi:10.1016/j.neucom.2015.10.111
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      Benicasa AX, Quiles MG, Silva TC, Liang Z, Romero RAF. An object-based visual selection framework [Internet]. Neurocomputing. 2016 ; 180 35-54.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.neucom.2015.10.111
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      Benicasa AX, Quiles MG, Silva TC, Liang Z, Romero RAF. An object-based visual selection framework [Internet]. Neurocomputing. 2016 ; 180 35-54.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.neucom.2015.10.111
  • Source: Information Sciences. Unidade: FFCLRP

    Subjects: INTELIGÊNCIA ARTIFICIAL, REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL

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      SILVA, Thiago Christiano e LIANG, Zhao. High-level pattern-based classification via tourist walks in networks. Information Sciences, v. 294, p. 109-126, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2014.09.048. Acesso em: 19 ago. 2024.
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      Silva, T. C., & Liang, Z. (2015). High-level pattern-based classification via tourist walks in networks. Information Sciences, 294, 109-126. doi:10.1016/j.ins.2014.09.048
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      Silva TC, Liang Z. High-level pattern-based classification via tourist walks in networks [Internet]. Information Sciences. 2015 ; 294 109-126.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.ins.2014.09.048
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      Silva TC, Liang Z. High-level pattern-based classification via tourist walks in networks [Internet]. Information Sciences. 2015 ; 294 109-126.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.ins.2014.09.048
  • Source: Neural Computing & Applications. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS

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      CUPERTINO, Thiago H e SILVA, Thiago C e LIANG, Zhao. Classification of multiple observation sets via network modularity. Neural Computing & Applications, v. 23, n. 7-8, p. 1923-1929, 2013Tradução . . Disponível em: https://doi.org/10.1007/s00521-012-1115-y. Acesso em: 19 ago. 2024.
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      Cupertino, T. H., Silva, T. C., & Liang, Z. (2013). Classification of multiple observation sets via network modularity. Neural Computing & Applications, 23( 7-8), 1923-1929. doi:10.1007/s00521-012-1115-y
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      Cupertino TH, Silva TC, Liang Z. Classification of multiple observation sets via network modularity [Internet]. Neural Computing & Applications. 2013 ; 23( 7-8): 1923-1929.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1007/s00521-012-1115-y
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      Cupertino TH, Silva TC, Liang Z. Classification of multiple observation sets via network modularity [Internet]. Neural Computing & Applications. 2013 ; 23( 7-8): 1923-1929.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1007/s00521-012-1115-y
  • Source: Soft Computing. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS

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      BREVE, Fabricio e LIANG, Zhao. Fuzzy community structure detection by particle competition and cooperation. Soft Computing, v. 17, n. 4, p. 659-673, 2013Tradução . . Disponível em: https://doi.org/10.1007/s00500-012-0924-3. Acesso em: 19 ago. 2024.
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      Breve, F., & Liang, Z. (2013). Fuzzy community structure detection by particle competition and cooperation. Soft Computing, 17( 4), 659-673. doi:10.1007/s00500-012-0924-3
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      Breve F, Liang Z. Fuzzy community structure detection by particle competition and cooperation [Internet]. Soft Computing. 2013 ; 17( 4): 659-673.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1007/s00500-012-0924-3
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      Breve F, Liang Z. Fuzzy community structure detection by particle competition and cooperation [Internet]. Soft Computing. 2013 ; 17( 4): 659-673.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1007/s00500-012-0924-3
  • Source: Neural Networks. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      SILVA, Thiago Christiano e LIANG, Zhao. Detecting and preventing error propagation via competitive learning. Neural Networks, v. 41, p. 70-84, 2013Tradução . . Disponível em: https://doi.org/10.1016/j.neunet.2012.11.001. Acesso em: 19 ago. 2024.
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      Silva, T. C., & Liang, Z. (2013). Detecting and preventing error propagation via competitive learning. Neural Networks, 41, 70-84. doi:10.1016/j.neunet.2012.11.001
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      Silva TC, Liang Z. Detecting and preventing error propagation via competitive learning [Internet]. Neural Networks. 2013 ; 41 70-84.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.neunet.2012.11.001
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      Silva TC, Liang Z. Detecting and preventing error propagation via competitive learning [Internet]. Neural Networks. 2013 ; 41 70-84.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.neunet.2012.11.001
  • Source: Neural Networks. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      XIAOMING, Liang e LIANG, Zhao. Phase-disorder-induced firing activity in excitable neuronal networks with attractive and repulsive coupling. Neural Networks, v. no 2012, p. 40-45, 2012Tradução . . Disponível em: https://doi.org/10.1016/j.neunet.2012.08.002. Acesso em: 19 ago. 2024.
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      Xiaoming, L., & Liang, Z. (2012). Phase-disorder-induced firing activity in excitable neuronal networks with attractive and repulsive coupling. Neural Networks, no 2012, 40-45. doi:10.1016/j.neunet.2012.08.002
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      Xiaoming L, Liang Z. Phase-disorder-induced firing activity in excitable neuronal networks with attractive and repulsive coupling [Internet]. Neural Networks. 2012 ; no 2012 40-45.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.neunet.2012.08.002
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      Xiaoming L, Liang Z. Phase-disorder-induced firing activity in excitable neuronal networks with attractive and repulsive coupling [Internet]. Neural Networks. 2012 ; no 2012 40-45.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.neunet.2012.08.002
  • Source: Information Sciences. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, INTELIGÊNCIA ARTIFICIAL, SISTEMAS DINÂMICOS

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      BERTINI JÚNIOR, João Roberto et al. A nonparametric classification method based on K-associated graphs. Information Sciences, v. 181, n. 24, p. 5435-5456, 2011Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2011.07.043. Acesso em: 19 ago. 2024.
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      Bertini Júnior, J. R., Liang, Z., Motta, R., & Lopes, A. de A. (2011). A nonparametric classification method based on K-associated graphs. Information Sciences, 181( 24), 5435-5456. doi:10.1016/j.ins.2011.07.043
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      Bertini Júnior JR, Liang Z, Motta R, Lopes A de A. A nonparametric classification method based on K-associated graphs [Internet]. Information Sciences. 2011 ; 181( 24): 5435-5456.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.ins.2011.07.043
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      Bertini Júnior JR, Liang Z, Motta R, Lopes A de A. A nonparametric classification method based on K-associated graphs [Internet]. Information Sciences. 2011 ; 181( 24): 5435-5456.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1016/j.ins.2011.07.043
  • Source: Physical Review E. Unidade: ICMC

    Assunto: REDES NEURAIS

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      LIANG, Xiaoming et al. Phase-disorder-induced double resonance of neuronal activity. Physical Review E, v. 82, n. 1, p. 010902_1-010902_4, 2010Tradução . . Disponível em: https://doi.org/10.1103/physreve.82.010902. Acesso em: 19 ago. 2024.
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      Liang, X., Liu, Z., Dhamala, M., & Zhao, L. (2010). Phase-disorder-induced double resonance of neuronal activity. Physical Review E, 82( 1), 010902_1-010902_4. doi:10.1103/physreve.82.010902
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      Liang X, Liu Z, Dhamala M, Zhao L. Phase-disorder-induced double resonance of neuronal activity [Internet]. Physical Review E. 2010 ; 82( 1): 010902_1-010902_4.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1103/physreve.82.010902
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      Liang X, Liu Z, Dhamala M, Zhao L. Phase-disorder-induced double resonance of neuronal activity [Internet]. Physical Review E. 2010 ; 82( 1): 010902_1-010902_4.[citado 2024 ago. 19 ] Available from: https://doi.org/10.1103/physreve.82.010902
  • 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: 19 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. 19 ] Available from: https://doi.org/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. 19 ] Available from: https://doi.org/10.1016/j.neunet.2009.06.027

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