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Artigo de periodico
The time lag in local field potential signals for the development of its Bayesian belief network (2024)
Tsukahara, Victor Hugo Batista; Oliveira Júnior, Jordão Natal de; Prizon, Tamiris; Ruggiero, Rafael Naime ; Maciel, Carlos Dias
Source: Eurasip Journal on Advances in Signal Processing. Unidades: EESC, FMRP
Subjects: INFERÊNCIA BAYESIANA, GEOMETRIA E MODELAGEM COMPUTACIONAL, TEORIA DA INFORMAÇÃO, ANÁLISE DE SÉRIES TEMPORAIS, SINCRONIZAÇÃO
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ABNT
TSUKAHARA, Victor Hugo Batista et al. The time lag in local field potential signals for the development of its Bayesian belief network. Eurasip Journal on Advances in Signal Processing, v. 87, 2024Tradução . . Disponível em: http://dx.doi.org/10.1186/s13634-024-01165-9. Acesso em: 03 dez. 2025.
APA
Tsukahara, V. H. B., Oliveira Júnior, J. N. de, Prizon, T., Ruggiero, R. N., & Maciel, C. D. (2024). The time lag in local field potential signals for the development of its Bayesian belief network. Eurasip Journal on Advances in Signal Processing, 87. doi:10.1186/s13634-024-01165-9
NLM
Tsukahara VHB, Oliveira Júnior JN de, Prizon T, Ruggiero RN, Maciel CD. The time lag in local field potential signals for the development of its Bayesian belief network [Internet]. Eurasip Journal on Advances in Signal Processing. 2024 ; 87[citado 2025 dez. 03 ] Available from: http://dx.doi.org/10.1186/s13634-024-01165-9
Vancouver
Tsukahara VHB, Oliveira Júnior JN de, Prizon T, Ruggiero RN, Maciel CD. The time lag in local field potential signals for the development of its Bayesian belief network [Internet]. Eurasip Journal on Advances in Signal Processing. 2024 ; 87[citado 2025 dez. 03 ] Available from: http://dx.doi.org/10.1186/s13634-024-01165-9
Tese (Doutorado)
Dynamic evaluation of induced epilepsy in rats: a bayesian network perspective (2022)
Tsukahara, Victor Hugo Batista; Maciel, Carlos Dias (Orientador)
Unidade: EESC
Subjects: ELETROENCEFALOGRAFIA, EPILEPSIA, INTELIGÊNCIA ARTIFICIAL, ALGORITMOS
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ABNT
TSUKAHARA, Victor Hugo Batista. Dynamic evaluation of induced epilepsy in rats: a bayesian network perspective. 2022. Tese (Doutorado) – Universidade de São Paulo, São Carlos, 2022. Disponível em: https://www.teses.usp.br/teses/disponiveis/18/18153/tde-19122022-123219/. Acesso em: 03 dez. 2025.
APA
Tsukahara, V. H. B. (2022). Dynamic evaluation of induced epilepsy in rats: a bayesian network perspective (Tese (Doutorado). Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/18/18153/tde-19122022-123219/
NLM
Tsukahara VHB. Dynamic evaluation of induced epilepsy in rats: a bayesian network perspective [Internet]. 2022 ;[citado 2025 dez. 03 ] Available from: https://www.teses.usp.br/teses/disponiveis/18/18153/tde-19122022-123219/
Vancouver
Tsukahara VHB. Dynamic evaluation of induced epilepsy in rats: a bayesian network perspective [Internet]. 2022 ;[citado 2025 dez. 03 ] Available from: https://www.teses.usp.br/teses/disponiveis/18/18153/tde-19122022-123219/
Artigo de periodico
Data-driven network dynamical model of rat brains during acute ictogenesis (2022)
Tsukahara, Victor Hugo Batista; Oliveira Júnior, Jordão Natal de; Barth, Vitor Bruno de Oliveira; Oliveira, Jasiara Carla de; Cota, Vinicius Rosa ; Maciel, Carlos Dias
Source: Frontiers in Neural Circuits. Unidade: EESC
Subjects: EPILEPSIA, INFERÊNCIA BAYESIANA, ENGENHARIA ELÉTRICA
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ABNT
TSUKAHARA, Victor Hugo Batista et al. Data-driven network dynamical model of rat brains during acute ictogenesis. Frontiers in Neural Circuits, v. 16, p. 1-13, 2022Tradução . . Disponível em: https://doi.org/10.3389/fncir.2022.747910. Acesso em: 03 dez. 2025.
APA
Tsukahara, V. H. B., Oliveira Júnior, J. N. de, Barth, V. B. de O., Oliveira, J. C. de, Cota, V. R., & Maciel, C. D. (2022). Data-driven network dynamical model of rat brains during acute ictogenesis. Frontiers in Neural Circuits, 16, 1-13. doi:10.3389/fncir.2022.747910
NLM
Tsukahara VHB, Oliveira Júnior JN de, Barth VB de O, Oliveira JC de, Cota VR, Maciel CD. Data-driven network dynamical model of rat brains during acute ictogenesis [Internet]. Frontiers in Neural Circuits. 2022 ; 16 1-13.[citado 2025 dez. 03 ] Available from: https://doi.org/10.3389/fncir.2022.747910
Vancouver
Tsukahara VHB, Oliveira Júnior JN de, Barth VB de O, Oliveira JC de, Cota VR, Maciel CD. Data-driven network dynamical model of rat brains during acute ictogenesis [Internet]. Frontiers in Neural Circuits. 2022 ; 16 1-13.[citado 2025 dez. 03 ] Available from: https://doi.org/10.3389/fncir.2022.747910
Artigo de periodico
Survival analysis of nonperiodic stimulation (NPS) performance (2021)
Tsukahara, Victor Hugo Batista; Oliveira, Jasiara Carla de; Cota, Vinicius Rosa ; Maciel, Carlos Dias
Source: Epilepsy & Behavior. Unidade: EESC
Subjects: EPILEPSIA, CONVULSÕES, ESTIMULAÇÃO ELÉTRICA, TESTES DE HIPÓTESES
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ABNT
TSUKAHARA, Victor Hugo Batista et al. Survival analysis of nonperiodic stimulation (NPS) performance. Epilepsy & Behavior, v. 122, 2021Tradução . . Disponível em: http://dx.doi.org/10.1016/j.yebeh.2021.108166. Acesso em: 03 dez. 2025.
APA
Tsukahara, V. H. B., Oliveira, J. C. de, Cota, V. R., & Maciel, C. D. (2021). Survival analysis of nonperiodic stimulation (NPS) performance. Epilepsy & Behavior, 122. doi:10.1016/j.yebeh.2021.108166
NLM
Tsukahara VHB, Oliveira JC de, Cota VR, Maciel CD. Survival analysis of nonperiodic stimulation (NPS) performance [Internet]. Epilepsy & Behavior. 2021 ; 122[citado 2025 dez. 03 ] Available from: http://dx.doi.org/10.1016/j.yebeh.2021.108166
Vancouver
Tsukahara VHB, Oliveira JC de, Cota VR, Maciel CD. Survival analysis of nonperiodic stimulation (NPS) performance [Internet]. Epilepsy & Behavior. 2021 ; 122[citado 2025 dez. 03 ] Available from: http://dx.doi.org/10.1016/j.yebeh.2021.108166
Artigo de periodico
Entropy: from thermodynamics to information processing (2021)
Natal, Jordão; Ávila, Ivonete; Tsukahara, Victor Hugo Batista; Pinheiro, Marcelo; Maciel, Carlos Dias
Source: Entropy. Unidade: EESC
Subjects: ENTROPIA, TERMODINÂMICA, ENGENHARIA ELÉTRICA
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ABNT
NATAL, Jordão et al. Entropy: from thermodynamics to information processing. Entropy, v. 23, p. 1-14, 2021Tradução . . Disponível em: https://doi.org/10.3390/e23101340. Acesso em: 03 dez. 2025.
APA
Natal, J., Ávila, I., Tsukahara, V. H. B., Pinheiro, M., & Maciel, C. D. (2021). Entropy: from thermodynamics to information processing. Entropy, 23, 1-14. doi:10.3390/e23101340
NLM
Natal J, Ávila I, Tsukahara VHB, Pinheiro M, Maciel CD. Entropy: from thermodynamics to information processing [Internet]. Entropy. 2021 ; 23 1-14.[citado 2025 dez. 03 ] Available from: https://doi.org/10.3390/e23101340
Vancouver
Natal J, Ávila I, Tsukahara VHB, Pinheiro M, Maciel CD. Entropy: from thermodynamics to information processing [Internet]. Entropy. 2021 ; 23 1-14.[citado 2025 dez. 03 ] Available from: https://doi.org/10.3390/e23101340
Trabalho de evento
Neural network classification, coherence and power spectrum analysis with stress database (2019)
Pedrino, Mateus C.; Arone, Rafael Augusto Caracciolo; Tsukahara, Victor Hugo Batista; Maciel, Carlos Dias
Source: Proceedings. Conference titles: Latin American Workshop on Computational Neuroscience - LAWCN. Unidade: EESC
Subjects: REDES NEURAIS, ELETROENCEFALOGRAFIA
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ABNT
PEDRINO, Mateus C. et al. Neural network classification, coherence and power spectrum analysis with stress database. 2019, Anais.. São João del-Rei: Escola de Engenharia de São Carlos, Universidade de São Paulo, 2019. Disponível em: https://repositorio.usp.br/directbitstream/676a53c5-d578-4c89-ad96-9a717eb2f345/sysno3185483_trabalho%2012%20-%20Neural%20Network%20Classification%2C%20Coherence%20and%20Power%20Spectrum%20Analysis%20with%20Stress%20Database.pdf. Acesso em: 03 dez. 2025.
APA
Pedrino, M. C., Arone, R. A. C., Tsukahara, V. H. B., & Maciel, C. D. (2019). Neural network classification, coherence and power spectrum analysis with stress database. In Proceedings. São João del-Rei: Escola de Engenharia de São Carlos, Universidade de São Paulo. Recuperado de https://repositorio.usp.br/directbitstream/676a53c5-d578-4c89-ad96-9a717eb2f345/sysno3185483_trabalho%2012%20-%20Neural%20Network%20Classification%2C%20Coherence%20and%20Power%20Spectrum%20Analysis%20with%20Stress%20Database.pdf
NLM
Pedrino MC, Arone RAC, Tsukahara VHB, Maciel CD. Neural network classification, coherence and power spectrum analysis with stress database [Internet]. Proceedings. 2019 ;[citado 2025 dez. 03 ] Available from: https://repositorio.usp.br/directbitstream/676a53c5-d578-4c89-ad96-9a717eb2f345/sysno3185483_trabalho%2012%20-%20Neural%20Network%20Classification%2C%20Coherence%20and%20Power%20Spectrum%20Analysis%20with%20Stress%20Database.pdf
Vancouver
Pedrino MC, Arone RAC, Tsukahara VHB, Maciel CD. Neural network classification, coherence and power spectrum analysis with stress database [Internet]. Proceedings. 2019 ;[citado 2025 dez. 03 ] Available from: https://repositorio.usp.br/directbitstream/676a53c5-d578-4c89-ad96-9a717eb2f345/sysno3185483_trabalho%2012%20-%20Neural%20Network%20Classification%2C%20Coherence%20and%20Power%20Spectrum%20Analysis%20with%20Stress%20Database.pdf
Trabalho de evento
Applying PDC for the recognition of firearm’s calibre (2019)
Ribeiro, Rafael Rodrigues Mendes ; Santos, Talysson Manoel de Oliveira; Gross, Tadeu Junior; Oliveira Júnior, Jordão Natal de; Tsukahara, Victor Hugo Batista; Maciel, Carlos Dias
Source: Anais. Conference titles: Simpósio Brasileiro de Automação Inteligente - SBAI. Unidade: EESC
Assunto: ARMA DE FOGO
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ABNT
RIBEIRO, Rafael Rodrigues Mendes et al. Applying PDC for the recognition of firearm’s calibre. 2019, Anais.. Campinas: Escola de Engenharia de São Carlos, Universidade de São Paulo, 2019. Disponível em: http://dx.doi.org/10.17648/sbai-2019-111498. Acesso em: 03 dez. 2025.
APA
Ribeiro, R. R. M., Santos, T. M. de O., Gross, T. J., Oliveira Júnior, J. N. de, Tsukahara, V. H. B., & Maciel, C. D. (2019). Applying PDC for the recognition of firearm’s calibre. In Anais. Campinas: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.17648/sbai-2019-111498
NLM
Ribeiro RRM, Santos TM de O, Gross TJ, Oliveira Júnior JN de, Tsukahara VHB, Maciel CD. Applying PDC for the recognition of firearm’s calibre [Internet]. Anais. 2019 ;[citado 2025 dez. 03 ] Available from: http://dx.doi.org/10.17648/sbai-2019-111498
Vancouver
Ribeiro RRM, Santos TM de O, Gross TJ, Oliveira Júnior JN de, Tsukahara VHB, Maciel CD. Applying PDC for the recognition of firearm’s calibre [Internet]. Anais. 2019 ;[citado 2025 dez. 03 ] Available from: http://dx.doi.org/10.17648/sbai-2019-111498
Trabalho de evento-anais periodico
Graph model evolution during epileptic seizures: linear model approach (2019)
Santos, Talysson Manoel de Oliveira; Tsukahara, Victor Hugo Batista; Oliveira, Jasiara C. de; Cota, Vinicius Rosa; Maciel, Carlos Dias
Source: Communications in Computer and Information Science. Conference titles: Latin American Workshop on Computational Neuroscience - LAWCN. Unidade: EESC
Subjects: ELETROENCEFALOGRAFIA, EPILEPSIA, PROCESSAMENTO DIGITAL DE SINAIS, ENGENHARIA ELÉTRICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Talysson Manoel de Oliveira et al. Graph model evolution during epileptic seizures: linear model approach. Communications in Computer and Information Science. Cham, Switzerland: Springer. Disponível em: https://doi.org/10.1007/978-3-030-36636-0_12. Acesso em: 03 dez. 2025. , 2019
APA
Santos, T. M. de O., Tsukahara, V. H. B., Oliveira, J. C. de, Cota, V. R., & Maciel, C. D. (2019). Graph model evolution during epileptic seizures: linear model approach. Communications in Computer and Information Science. Cham, Switzerland: Springer. doi:10.1007/978-3-030-36636-0_12
NLM
Santos TM de O, Tsukahara VHB, Oliveira JC de, Cota VR, Maciel CD. Graph model evolution during epileptic seizures: linear model approach [Internet]. Communications in Computer and Information Science. 2019 ; 1068 20-29.[citado 2025 dez. 03 ] Available from: https://doi.org/10.1007/978-3-030-36636-0_12
Vancouver
Santos TM de O, Tsukahara VHB, Oliveira JC de, Cota VR, Maciel CD. Graph model evolution during epileptic seizures: linear model approach [Internet]. Communications in Computer and Information Science. 2019 ; 1068 20-29.[citado 2025 dez. 03 ] Available from: https://doi.org/10.1007/978-3-030-36636-0_12

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