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Artigo de periodico
Adaptive Kalman filter-based information fusion in electricalimpedance tomography for a two-phase flow (2021)
Pellegrini, Sérgio de Paula ; Trigo, Flávio Celso ; González Lima, Raúl
Fonte: Mechanical Systems and Signal Processing. Unidade: EP
Assuntos: PROBLEMAS INVERSOS, FILTROS DE KALMAN, IMPEDÂNCIA ELÉTRICA, TOMOGRAFIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PELLEGRINI, Sérgio de Paula e TRIGO, Flávio Celso e GONZÁLEZ LIMA, Raúl. Adaptive Kalman filter-based information fusion in electricalimpedance tomography for a two-phase flow. Mechanical Systems and Signal Processing, v. 150, p. 1-21, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.ymssp.2020.107326. Acesso em: 07 nov. 2024.
APA
Pellegrini, S. de P., Trigo, F. C., & González Lima, R. (2021). Adaptive Kalman filter-based information fusion in electricalimpedance tomography for a two-phase flow. Mechanical Systems and Signal Processing, 150, 1-21. doi:10.1016/j.ymssp.2020.107326
NLM
Pellegrini S de P, Trigo FC, González Lima R. Adaptive Kalman filter-based information fusion in electricalimpedance tomography for a two-phase flow [Internet]. Mechanical Systems and Signal Processing. 2021 ; 150 1-21.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1016/j.ymssp.2020.107326
Vancouver
Pellegrini S de P, Trigo FC, González Lima R. Adaptive Kalman filter-based information fusion in electricalimpedance tomography for a two-phase flow [Internet]. Mechanical Systems and Signal Processing. 2021 ; 150 1-21.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1016/j.ymssp.2020.107326
Artigo de periodico
An inner–outer nonlinear programming approach for constrained quadratic matrix model updating (2016)
Andretta, Marina ; Birgin, Ernesto Julian Goldberg ; Raydan, Marcos
Fonte: Mechanical Systems and Signal Processing. Unidades: ICMC, IME
Assuntos: ALGORITMOS, PROGRAMAÇÃO NÃO LINEAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ANDRETTA, Marina e BIRGIN, Ernesto Julian Goldberg e RAYDAN, Marcos. An inner–outer nonlinear programming approach for constrained quadratic matrix model updating. Mechanical Systems and Signal Processing, v. 66-67, n. Ja 2016, p. 78-88, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.ymssp.2015.05.002. Acesso em: 07 nov. 2024.
APA
Andretta, M., Birgin, E. J. G., & Raydan, M. (2016). An inner–outer nonlinear programming approach for constrained quadratic matrix model updating. Mechanical Systems and Signal Processing, 66-67( Ja 2016), 78-88. doi:10.1016/j.ymssp.2015.05.002
NLM
Andretta M, Birgin EJG, Raydan M. An inner–outer nonlinear programming approach for constrained quadratic matrix model updating [Internet]. Mechanical Systems and Signal Processing. 2016 ; 66-67( Ja 2016): 78-88.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1016/j.ymssp.2015.05.002
Vancouver
Andretta M, Birgin EJG, Raydan M. An inner–outer nonlinear programming approach for constrained quadratic matrix model updating [Internet]. Mechanical Systems and Signal Processing. 2016 ; 66-67( Ja 2016): 78-88.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1016/j.ymssp.2015.05.002
Artigo de periodico
Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach (2014)
Trigo, Flávio Celso ; Martins, Flavius Portella Ribas ; Fleury, Agenor de Toledo ; Silva Junior, Helio Correa da
Fonte: Mechanical Systems and Signal Processing. Unidade: EP
Assuntos: FILTROS DE KALMAN, VISÃO COMPUTACIONAL, TUBOS FLEXÍVEIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TRIGO, Flávio Celso et al. Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach. Mechanical Systems and Signal Processing, v. 43, n. 1/2 p. 124-140, 2014Tradução . . Disponível em: http://ac.els-cdn.com/S0888327013005086/1-s2.0-S0888327013005086-main.pdf?_tid=99b123f6-6e78-11e4-9c44-00000aacb362&acdnat=1416242678_8edb2b93efaf957d6356cd12da75ea2d. Acesso em: 07 nov. 2024.
APA
Trigo, F. C., Martins, F. P. R., Fleury, A. de T., & Silva Junior, H. C. da. (2014). Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach. Mechanical Systems and Signal Processing, 43( 1/2 p. 124-140). doi:10.1016/j.ymssp.2014.01.001
NLM
Trigo FC, Martins FPR, Fleury A de T, Silva Junior HC da. Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach [Internet]. Mechanical Systems and Signal Processing. 2014 ; 43( 1/2 p. 124-140):[citado 2024 nov. 07 ] Available from: http://ac.els-cdn.com/S0888327013005086/1-s2.0-S0888327013005086-main.pdf?_tid=99b123f6-6e78-11e4-9c44-00000aacb362&acdnat=1416242678_8edb2b93efaf957d6356cd12da75ea2d
Vancouver
Trigo FC, Martins FPR, Fleury A de T, Silva Junior HC da. Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach [Internet]. Mechanical Systems and Signal Processing. 2014 ; 43( 1/2 p. 124-140):[citado 2024 nov. 07 ] Available from: http://ac.els-cdn.com/S0888327013005086/1-s2.0-S0888327013005086-main.pdf?_tid=99b123f6-6e78-11e4-9c44-00000aacb362&acdnat=1416242678_8edb2b93efaf957d6356cd12da75ea2d
Artigo de periodico
Hybrid time-frequency methods for non-stationary mechanical signal analysis (2004)
Padovese, Linilson Rodrigues
Fonte: Mechanical Systems and Signal Processing. Unidade: EP
Assuntos: PROCESSAMENTO DE SINAIS, SISTEMAS MECÂNICOS, VIBRAÇÕES DE MÁQUINAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PADOVESE, Linilson Rodrigues. Hybrid time-frequency methods for non-stationary mechanical signal analysis. Mechanical Systems and Signal Processing, v. 18, n. 5, p. 1047-1064, 2004Tradução . . Disponível em: https://doi.org/10.1016/j.ymssp.2003.12.003. Acesso em: 07 nov. 2024.
APA
Padovese, L. R. (2004). Hybrid time-frequency methods for non-stationary mechanical signal analysis. Mechanical Systems and Signal Processing, 18( 5), 1047-1064. doi:10.1016/j.ymssp.2003.12.003
NLM
Padovese LR. Hybrid time-frequency methods for non-stationary mechanical signal analysis [Internet]. Mechanical Systems and Signal Processing. 2004 ;18( 5): 1047-1064.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1016/j.ymssp.2003.12.003
Vancouver
Padovese LR. Hybrid time-frequency methods for non-stationary mechanical signal analysis [Internet]. Mechanical Systems and Signal Processing. 2004 ;18( 5): 1047-1064.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1016/j.ymssp.2003.12.003

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