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Relevant bibliographies by topics / Kalman-Bucy Filter

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Academic literature on the topic 'Kalman-Bucy Filter'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Kalman-Bucy Filter"

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George, Jemin. "Robust Kalman-Bucy Filter." IEEE Transactions on Automatic Control 58, no. 1 (2013): 174–80. http://dx.doi.org/10.1109/tac.2012.2203052.

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Tovstik, Tatiana M., and Petr E. Tovstik. "Linear generalized Kalman-Bucy filter." Vestnik of Saint Petersburg University. Mathematics. Mechanics. Astronomy 6(64), no. 4 (2019): 636–45. http://dx.doi.org/10.21638/11701/spbu01.2019.409.

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Johnson, Russell, and Carmen Núñez. "The Kalman-Bucy filter revisited." Discrete and Continuous Dynamical Systems 34, no. 10 (2014): 4139–53. http://dx.doi.org/10.3934/dcds.2014.34.4139.

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Bergemann, Kay, and Sebastian Reich. "An ensemble Kalman-Bucy filter for continuous data assimilation." Meteorologische Zeitschrift 21, no. 3 (2012): 213–19. http://dx.doi.org/10.1127/0941-2948/2012/0307.

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Allan, Andrew L., and Samuel N. Cohen. "Parameter Uncertainty in the Kalman--Bucy Filter." SIAM Journal on Control and Optimization 57, no. 3 (2019): 1646–71. http://dx.doi.org/10.1137/18m1167693.

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Basin, Michael V. "On filtering over Îto-Volterra observations." Journal of Applied Mathematics and Stochastic Analysis 13, no. 4 (2000): 347–64. http://dx.doi.org/10.1155/s1048953300000319.

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In this paper, the Kalman-Bucy filter is designed for an Îto-Volterra process over Ito-Volterra observations that cannot be reduced to the case of a differential observation equation. The Kalman-Bucy filter is then designed for an Ito-Volterra process over discontinuous Ito-Volterra observations. Based on the obtained results, the filtering problem over discrete observations with delays is solved. Proofs of the theorems substantiating the filtering algorithms are given.

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Farias, Valcir, Marcus Rocha, and Heliton Tavares. "Application of the Kalman Filter in Functional Magnetic Resonance Image Data." International Journal for Innovation Education and Research 8, no. 9 (2020): 416–33. http://dx.doi.org/10.31686/ijier.vol8.iss9.2657.

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The Kalman-Bucy filter was applied on the preprocessing of the functional magnetic resonance image-fMRI. Numerical simulations of hemodynamic response added Gaussian noise were performed to evaluate the performance of the filter. After the proceeding was applied in auditory real data. The Kohonen’s self-organized map was employed as tools to compare the performance of the Kalman’s filter with another type of pre-processing. The results of the application of Kalman-Bucy filter for simulated data and real auditory data showed that it can be used as a tool in the temporal filtering step in fMRI d

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Tovstik, Tatiana M. "Linear Kalman-Bucy filter with vector autoregressive signal and noise." Vestnik of Saint Petersburg University. Mathematics. Mechanics. Astronomy 8, no. 1 (2021): 111–22. http://dx.doi.org/10.21638/spbu01.2021.110.

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The linear Kalman-Bucy filter problem for a system, at that a signal and a noise are vector independent stationary autoregressive processes with orders larger than 1, is investigated. The recurrent equations for filter and its error are delivered. The optimal way of the initial data definition is proposed. Some numerical examples are given. In one of them the algorithm leads to a stationary behavior at infinity. In the other example the Kalman- Bucy filter is impossible because the filter error goes to infinity. A behavior of a signal and its error is illustrated by a simulation of a signal an

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Harvey, A. C., and James H. Stock. "The Estimation of Higher-Order Continuous Time Autoregressive Models." Econometric Theory 1, no. 1 (1985): 97–117. http://dx.doi.org/10.1017/s0266466600011026.

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A method is presented for computing maximum likelihood, or Gaussian, estimators of the structural parameters in a continuous time system of higherorder stochastic differential equations. It is argued that it is computationally efficient in the standard case of exact observations made at equally spaced intervals. Furthermore it can be applied in situations where the observations are at unequally spaced intervals, some observations are missing and/or the endogenous variables are subject to measurement error. The method is based on a state space representation and the use of the Kalman–Bucy filte

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Tovstik, T. M. "Linear Kalman–Bucy Filter with Autoregressive Signal and Noise." Vestnik St. Petersburg University, Mathematics 51, no. 3 (2018): 276–85. http://dx.doi.org/10.3103/s1063454118030093.

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Dissertations / Theses on the topic "Kalman-Bucy Filter"

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Castro, Eduardo da Silva. "Avaliação de algoritmos numéricos aplicados ao controle ativo de vibrações mecânicas." Universidade Federal de Juiz de Fora (UFJF), 2011. https://repositorio.ufjf.br/jspui/handle/ufjf/3534.

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Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-03-03T13:37:53Z No. of bitstreams: 1 eduardodasilvacastro.pdf: 10234661 bytes, checksum: c58d694820eabc593fe5f1b06aa4f93d (MD5)<br>Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-03-06T20:14:38Z (GMT) No. of bitstreams: 1 eduardodasilvacastro.pdf: 10234661 bytes, checksum: c58d694820eabc593fe5f1b06aa4f93d (MD5)<br>Made available in DSpace on 2017-03-06T20:14:38Z (GMT). No. of bitstreams: 1 eduardodasilvacastro.pdf: 10234661 bytes, checksum: c58d694820eabc593fe5f1b06aa4f93d (MD5) Previous

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ROCHA, Marcus Pinto da Costa da. "Atenuação de múltiplas e compressão do pulso fonte em dados de sísmica de reflexão utilizando o filtro Kalman-Bucy." Universidade Federal do Pará, 2003. http://repositorio.ufpa.br/jspui/handle/2011/5747.

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Submitted by Cleide Dantas (cleidedantas@ufpa.br) on 2014-05-20T12:07:56Z No. of bitstreams: 2 license_rdf: 23898 bytes, checksum: e363e809996cf46ada20da1accfcd9c7 (MD5) Tese_AtenuacaoMultiplasCompressao.pdf: 24452115 bytes, checksum: 8631331284b78acc0b168236fbe6c6ea (MD5)<br>Rejected by Irvana Coutinho (irvana@ufpa.br), reason: Ausência de palavras-chave on 2014-08-07T12:42:09Z (GMT)<br>Submitted by Cleide Dantas (cleidedantas@ufpa.br) on 2014-09-10T15:30:42Z No. of bitstreams: 2 license_rdf: 23898 bytes, checksum: e363e809996cf46ada20da1accfcd9c7 (MD5) Tese_AtenuacaoMultiplasCompress

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Rizzo, Alessandro. "Il problema del filtraggio con applicazione in finanza." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21792/.

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In diversi problemi di analisi di dati reali risulta opportuno stimare quantità non note sulla base di una successione di osservazioni, affette da rumore o poco precise, che si rendono disponibili in modo sequenziale nel tempo. Spesso, situazioni di questo tipo si hanno quando il modello utilizzato per la descrizione del fenomeno preso in considerazione è un sistema dinamico con componenti non direttamente osservabili. Tali modelli sono descritti da due equazioni: la prima descrive l'effettiva evoluzione del sistema (lo stato) e la seconda specifica la relazione che lega le osservazioni con lo

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ROCHA, Marcus Pinto da Costa da. "Aplicação do método de Kalman a dados geofísicos." Universidade Federal do Pará, 1998. http://repositorio.ufpa.br/jspui/handle/2011/5786.

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Submitted by Cleide Dantas (cleidedantas@ufpa.br) on 2014-06-09T12:19:45Z No. of bitstreams: 2 license_rdf: 23898 bytes, checksum: e363e809996cf46ada20da1accfcd9c7 (MD5) Dissertacao_AplicacaoMetodoKalman.pdf: 5931360 bytes, checksum: 9d5bc90e28509e1df9337a46bafe80c4 (MD5)<br>Rejected by Irvana Coutinho (irvana@ufpa.br), reason: Indexar os assuntos on 2014-08-06T14:42:05Z (GMT)<br>Submitted by Cleide Dantas (cleidedantas@ufpa.br) on 2014-08-11T13:45:39Z No. of bitstreams: 2 license_rdf: 23898 bytes, checksum: e363e809996cf46ada20da1accfcd9c7 (MD5) Dissertacao_AplicacaoMetodoKalman.pdf: 59

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Kubelka, Vít. "Filtrace stochastických evolučních rovnic." Doctoral thesis, 2020. http://www.nusl.cz/ntk/nusl-437014.

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Filtering for Stochastic Evolution Equations Vít Kubelka Doctoral thesis Abstract Linear filtering problem for infinite-dimensional Gaussian processes is studied, the observation process being finite-dimensional. Integral equations for the filter and for covariance of the error are derived. General results are applied to linear SPDEs driven by Gauss-Volterra process observed at finitely many points of the domain and to delayed SPDEs driven by white noise. Subsequently, the continuous dependence of the filter and observation error on parameters which may be present both in the signal and the ob

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Týbl, Ondřej. "Kalmanův-Bucyho filtr ve spojitém čase." Master's thesis, 2019. http://www.nusl.cz/ntk/nusl-397771.

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In the Thesis we study the problem of linear filtration of Gaussian signals in finite-dimensional space. We use the Kalman-type equations for the filter to show that the filter depends continuously on the signal. Secondly, we show the same continuity property for the covariance of the error and verify existence and uniqueness of a solution to an integral equation that is satisfied by the filter even under more general assumptions. We present several examples of application of the continuity property that are based on the theory of stochastic differential equations driven by fractional Brownian

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Maia, Nuno Filipe Laureano. "Estimação de incertezas em modelos dinâmicos pelo método de filtragem de Kalman-Bucy." Master's thesis, 2009. http://hdl.handle.net/10400.6/3618.

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A presente Dissertação visa a estimação de incertezas em modelos dinâmicos através de filtros de Kalman-Bucy. Foram estudados vários tipos de filtro de Kalman, sendo que o filtro de Kalman clássico tem a particularidade de requerer um conhecimento das características estocásticas do sistema. Porém nem sempre é possível obter essas características, dado o desconhecimento do sistema, facto que acontece na maior parte das vezes no que diz respeito a aplicações em aeronáutica Deste modo, foi reinterpretado o filtro de Kalman-Bucy no espaço dual, com o objectivo de flexibilizar o uso deste método,

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Costa, Mariana Elisa Moreira Nunes da. "Orientação de mísseis intercetores com base no método dos Reguladores Quadráticos Lineares (LQR) com estimação de trajetórias." Master's thesis, 2017. http://hdl.handle.net/10400.6/7925.

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Desde a Segunda Guerra Mundial, o desenvolvimento de tecnologia no setor de mísseis tem vindo a representar um fator que pode ser determinante no rumo da Humanidade. Devido à importância que constitui, este é um dos se tores mais desafiantes a ser investigado. Com esta dissertação, pretende-se incrementar alguns fundamentos em duas das áreas mais cen trais à atuação do míss il: leis de orien tação e localização precisa do alvo. Assim sendo, na primeira área referida são exploradas as leis de orientação a partir das trajetórias efetuadas pelo míssil de encontro ao alvo com base nas diretr

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Books on the topic "Kalman-Bucy Filter"

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Brammer, Karl. Kalman-Bucy filters. Artech House, 1989.

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Book chapters on the topic "Kalman-Bucy Filter"

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Kroschel, Kristian. "Kalman-Bucy-Filter." In Statistische Nachrichtentheorie. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-662-10046-2_5.

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Ruymgaart, Peter A., and Tsu T. Soong. "The Kalman-Bucy Filter." In Mathematics of Kalman-Bucy Filtering. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73341-3_4.

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Ruymgaart, Peter A., and Tsu T. Soong. "The Kalman-Bucy Filter." In Mathematics of Kalman-Bucy Filtering. Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-96842-6_4.

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Zhao, Jin, Rongchen Zhao, and Feng He. "Vehicle Lateral States Estimation Using Kalman-Bucy Filter." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33795-6_19.

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Johnson, Russell, Rafael Obaya, Sylvia Novo, Carmen Núñez, and Roberta Fabbri. "Nonautonomous Control Theory: Linear Regulator Problem and the Kalman–Bucy Filter." In Developments in Mathematics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29025-6_6.

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Osintcev, Mikhail, and Vladimir A. Sobolev. "Order Reduction of Kalman–Bucy Filter for Systems with Low Measurement Noise." In Trends in Mathematics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01153-6_9.

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Davis, Jon H. "Kalman-Bucy Filters." In Systems & Control: Foundations & Applications. Birkhäuser Boston, 2002. http://dx.doi.org/10.1007/978-1-4612-0071-0_5.

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Weinmann, Alexander. "Robustness of Observers and Kalman-Bucy Filters." In Uncertain Models and Robust Control. Springer Vienna, 1991. http://dx.doi.org/10.1007/978-3-7091-6711-3_18.

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Bougerol, Philippe. "Filtre de Kalman Bucy et exposants de Lyapounov." In Lecture Notes in Mathematics. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/bfb0086662.

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"Kalman-Bucy Filter." In Computer Vision. Springer US, 2014. http://dx.doi.org/10.1007/978-0-387-31439-6_100269.

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Conference papers on the topic "Kalman-Bucy Filter"

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Zhang, Xiaocheng, Wenchao Xue, Haitao Fang, and Xingkang He. "On Extended State Based Kalman-Bucy Filter." In 2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS). IEEE, 2018. http://dx.doi.org/10.1109/ddcls.2018.8515987.

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De Paula, Alesi Augusto, Víctor Costa da Silva Campos, Guilherme Vianna Raffo, and Bruno Otávio Soares Teixeira. "Novel Gaussian State Estimator based on H2 Norm and Steady-State Variance." In Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.1259.

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This paper proposes a novel state estimator for discrete-time linear systems with Gaussian noise. The proposed algorithm is a fixed-gain filter, whose observer structure is more general than Kalman one for linear time-invariant systems. Therefore, the steady-state variance of the estimation error is minimized. For white noise stochastic processes, this performance criterion is reduced to the square H2 norm of a given linear time-invariant system. Then, the proposed algorithm is called observer H2 filter (OH2F). This is the standard Wiener-Hopf or Kalman-Bucy filtering problem. As the Kalman pr

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de Melo, Flavio Eler, Jose F. B. Brancalion, and Karl Heinz Kienitz. "Augmentation to the Extended Kalman-Bucy filter for single target tracking." In 2010 13th International Conference on Information Fusion (FUSION 2010). IEEE, 2010. http://dx.doi.org/10.1109/icif.2010.5711830.

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Nakayama, Takayuki, and Hideo Fujimoto. "Stability analysis of output feedback receding horizon controller with Kalman-Bucy filter." In 2007 46th IEEE Conference on Decision and Control. IEEE, 2007. http://dx.doi.org/10.1109/cdc.2007.4435027.

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Maree, J. P., L. Imsland, and J. Jouffroy. "A convergence result for the unscented Kalman-Bucy filter using contraction theory." In 2013 European Control Conference (ECC). IEEE, 2013. http://dx.doi.org/10.23919/ecc.2013.6669183.

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Ramasubramanian, A., and L. R. Ray. "Adaptive friction compensation using extended Kalman-Bucy filter friction estimation: a comparative study." In Proceedings of 2000 American Control Conference (ACC 2000). IEEE, 2000. http://dx.doi.org/10.1109/acc.2000.878675.

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Fang, Song, Hideaki Ishii, Jie Chen, and Karl Henrik Johansson. "A Frequency-Domain Characterization of Optimal Error Covariance for the Kalman-Bucy Filter." In 2018 IEEE Conference on Decision and Control (CDC). IEEE, 2018. http://dx.doi.org/10.1109/cdc.2018.8619084.

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Szabo, Tomas, Michael Buchholz, and Klaus Dietmayer. "Optimal Control of a Gearshift With a Dual-Clutch Transmission." In ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control. ASMEDC, 2011. http://dx.doi.org/10.1115/dscc2011-6028.

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This paper presents a model for a heavy duty truck powertrain test rig with a dual-clutch transmission. For this powertrain model, an LQR controller is designed to compute the torque profiles for performing powershifts while both clutches are slipping. Since most of the system states are not measurable, a Kalman-Bucy filter is implemented to estimate the states. The controller and estimation performance will be discussed in detail using both simulation and measurement results.

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Rahimi Mousavi, Mir Saman, and Benoit Boulet. "Dynamical modeling and optimal state estimation using Kalman-Bucy filter for a seamless two-speed transmission for electric vehicles." In 2015 23th Mediterranean Conference on Control and Automation (MED). IEEE, 2015. http://dx.doi.org/10.1109/med.2015.7158732.

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Sandberg, Henrik, Jean-Charles Delvenne, Nigel J. Newton, and Sanjoy K. Mitter. "Thermodynamic costs in implementing Kalman-Bucy filters." In 2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2014. http://dx.doi.org/10.1109/allerton.2014.7028503.

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