Academic literature on the topic 'Continuous-Discrete filter'
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Journal articles on the topic "Continuous-Discrete filter"
Xia, Yuanqing, Zhihong Deng, Li Li, and Xiumei Geng. "A new continuous-discrete particle filter for continuous-discrete nonlinear systems." Information Sciences 242 (September 2013): 64–75. http://dx.doi.org/10.1016/j.ins.2013.04.030.
Full textLange, Theresa. "Derivation of ensemble Kalman–Bucy filters with unbounded nonlinear coefficients." Nonlinearity 35, no. 2 (December 31, 2021): 1061–92. http://dx.doi.org/10.1088/1361-6544/ac4337.
Full textSharma, Shambhu N., and H. Parthasarathy. "A two-body continuous-discrete filter." Nonlinear Dynamics 51, no. 1-2 (February 6, 2007): 155–70. http://dx.doi.org/10.1007/s11071-007-9199-0.
Full textHu, Haoran, Shuxin Chen, Hao Wu, and Renke He. "Robust Estimation in Continuous–Discrete Cubature Kalman Filters for Bearings-Only Tracking." Applied Sciences 12, no. 16 (August 15, 2022): 8167. http://dx.doi.org/10.3390/app12168167.
Full textMurata, Masaya, and Kaoru Hiramatsu. "Non-Gaussian Filter for Continuous-Discrete Models." IEEE Transactions on Automatic Control 64, no. 12 (December 2019): 5260–64. http://dx.doi.org/10.1109/tac.2019.2914953.
Full textKnudsen, Torben, and John Leth. "A New Continuous Discrete Unscented Kalman Filter." IEEE Transactions on Automatic Control 64, no. 5 (May 2019): 2198–205. http://dx.doi.org/10.1109/tac.2018.2867325.
Full textChubich, Vladimir, and Svetlana Kulabukhova. "Research on the effectiveness of continuous-discrete cubature Kalman filter robust modifications." Information and Control Systems, no. 4 (August 24, 2020): 11–19. http://dx.doi.org/10.31799/1684-8853-2020-4-11-19.
Full textRudenko, E. A. "Optimal continuous-discrete nonlinear finite memory filter with a discrete predictions." Journal of Computer and Systems Sciences International 55, no. 6 (November 2016): 878–93. http://dx.doi.org/10.1134/s1064230716050129.
Full textWeller, S. R., A. Feuer, G. C. Goodwin, and H. V. Poor. "Interrelations between continuous and discrete lattice filter structures." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 40, no. 11 (1993): 705–13. http://dx.doi.org/10.1109/82.251838.
Full textShald, Scott. "The continuous kalman filter as the limit of the discrete kalman filter." Stochastic Analysis and Applications 17, no. 5 (January 1999): 841–56. http://dx.doi.org/10.1080/07362999908809638.
Full textDissertations / Theses on the topic "Continuous-Discrete filter"
Allahyani, Seham. "Contributions to filtering under randomly delayed observations and additive-multiplicative noise." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/16297.
Full textIufereva, Olga. "Algorithmes de filtrage avec les observations distribuées par Poisson." Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. https://theses.hal.science/tel-04720020.
Full textFiltering theory basically relates to optimal state estimation in stochastic dynamical systems, particularly when faced with partial and noisy data. This field, closely intertwined with control theory, focuses on designing estimators doing real-time computation while maintaining an acceptable level of accuracy as measured by the mean square error. The necessity for such estimates becomes increasingly critical with the proliferation of network-controlled systems, such as autonomous vehicles and complex industrial processes, where the observation processes are subject to randomness in transmission and this gives rise to varying information patterns under which the estimation must be carried out.This thesis addresses the important task of state estimation in continuous-time stochastic dynamical systems when the observation process is available only at some discrete time instants governed by a random process. By adapting classical estimation methods, we derive equations for optimal state estimator, explore their properties and practicality, and propose and evaluates sub-optimal alternatives, showcasing parallels to the existing techniques within the classical estimation domain when applied to Poisson-distributed observation processes.The study covers three classes of mathematical models for the continuous-time dynamical system and the discrete observation process. First, we consider Ito-stochastic differential equations with Lipschitz drift terms and constant diffusion coefficient, whereas the lower-dimensional discrete observation process comprises the nonlinear mapping of the state and additive Gaussian noise. We propose easy-to-implement continuous-discrete suboptimal state estimators for this system class. Assuming that a Poisson counter governs discrete times at which the observations are available, we compute the expectation or error covariance process. Analysis is carried out to provide conditions for boundedness of the error covariance process, as well as, the dependence on the mean sampling rate.Secondly, we consider the dynamical systems described by continuous-time Markov chains with finite state space, and the observation process is obtained by discretizing a conventional stochastic process driven by a Wiener process. For this case, the $L_1$-convergence of the derived optimal estimator to the classical (purely continuous) optimal estimator (Wonham filter) is shown with respect to increasing intensity of Poisson processes.Lastly, we study continuous-discrete particle filters for Ornstein-Uhlenbeck processes with discrete observations described by linear functions of state and additive Gaussian noise. Particle filters have gained a lot of interest for state estimation in large-scale models with noisy measurements where the computation of optimal gain is either computationally expensive or not entirely feasible due to complexity of the dynamics. In this thesis, we propose continuous-discrete McKean–Vlasov type diffusion processes, which serve as the mean-field model for describing the particle dynamics. We study several kinds of mean-field processes depending on how the noise terms are included in mimicking the state process and the observation model. The resulting particles are coupled through empirical covariances which are updated at discrete times with the arrival of new observations. With appropriate analysis of the first and second moments, we show that under certain conditions on system parameters, the performance of the particle filters approaches the optimal filter as the number of particles gets larger
Boizot, Nicolas. "Adaptative high-gain extended Kalman filter and applications." Phd thesis, Université de Bourgogne, 2010. http://tel.archives-ouvertes.fr/tel-00559107.
Full textHavlíček, Martin. "Zkoumání konektivity mozkových sítí pomocí hemodynamického modelování." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-233576.
Full textOndra, Josef. "Komprese signálů EKG s využitím vlnkové transformace." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217209.
Full textTang, Ding-Chiang, and 唐鼎強. "Optimal design of 2-D digital filters and 1-D filter banks with continuous and discrete coefficients." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/15121517814866567712.
Full text國立臺灣大學
電機工程學系
86
Recently, digital filters and digital filter banks have played an important role on many digital signal processing theories and applications. In this thesis, we apply weighted least squares(WLS) algorithm and Karmarkar's algorithm as optimization tools to design 1-D Nonuniform-Division Maximally Decimated Filter Banks(NDMDFB) and 2-D FIR filters with continuous coefficients. Due to the circuit complexity and high cost of multibit multipliers while implementing an FIR filter of the conventional structure, we propose a new FIR filter structure whose main part consists of a transversal filter with tap coefficients restricted to -1,0,+1 and cascaded with a simple recursive section with some specific resetting function. Therefore, it's unnecessary for transversal filter to use multipliers, the configuration is suitable for hardware implementation. Based on the new structure, we design NDMDFB and 2-D FIR filter with coefficients -1,0,and +1. Design examples show the effectiveness of the proposed design technique in the thesis.
Boddikurapati, Sirish. "Sequential Monte Carlo Methods With Applications To Communication Channels." 2009. http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7537.
Full textWang, Yan. "Design techniques for wideband low-power Delta-Sigma analog-to-digital converters." Thesis, 2009. http://hdl.handle.net/1957/13664.
Full textGraduation date: 2010
Books on the topic "Continuous-Discrete filter"
H, Tranter William, and Fannin D. Ronald, eds. Signals and systems: Continuous and discrete. 4th ed. Upper Saddle River, NJ: Prentice Hall, 1998.
Find full textH, Tranter William, and Fannin D. Ronald, eds. Signals and systems: Continuous and discrete. 2nd ed. New York: Macmillan, 1989.
Find full textH, Tranter William, and Fannin D. Ronald, eds. Signals and systems: Continuous and discrete. 3rd ed. New York: Macmillan, 1993.
Find full text1935-, Srinath Mandyam D., ed. Continuous and discrete signals and systems. Englewood Cliffs, N.J: Prentice Hall, 1990.
Find full text1935-, Srinath Mandyam D., ed. Continuous and discrete signals and systems. 2nd ed. Upper Saddle River, NJ: Prentice Hall, 1998.
Find full text1935-, Srinath Mandyam D., ed. Continuous and discrete signals and systems. Englewood Cliffs,N.J: Prentice-Hall, 1990.
Find full textMcGillem, Clare D. Continuous and discrete signal and system analysis. 3rd ed. New York: Oxford University Press, 1991.
Find full textMcGillem, Clare D. Continuous and discrete signal and system analysis. 3rd ed. Philadelphia: Saunders College Pub., 1991.
Find full textTranter, William H., Rodger E. Ziemer, and D. R. Fannin. Signals and Systems : Pearson New International Edition: Continuous and Discrete. Pearson Education, Limited, 2013.
Find full textBook chapters on the topic "Continuous-Discrete filter"
Moschytz, George S. "From Continuous Time to Discrete Time." In Analog Circuit Theory and Filter Design in the Digital World, 369–80. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00096-7_14.
Full textImran, A., X. Wang, and X. Yue. "State and Covariance Matrix Propagation for Continuous-Discrete Extended Kalman Filter Using Modified Chebyshev Picard Iteration Method." In Computational and Experimental Simulations in Engineering, 141–49. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-02097-1_11.
Full textKhelifa, Chahinez Nour El Houda, and Abderrahim Belmadani. "New Approach for Continuous and Discrete Optimization: Optimization by Morphological Filters." In Heuristics for Optimization and Learning, 425–40. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58930-1_28.
Full textLancaster, Peter, and Leiba Rodman. "The Discrete Kalman Filter." In Algebraic Riccati Equations, 371–86. Oxford University PressOxford, 1995. http://dx.doi.org/10.1093/oso/9780198537953.003.0017.
Full textBerber, Stevan. "Sampling and Reconstruction of Continuous-Time Signals." In Discrete Communication Systems, 674–89. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198860792.003.0013.
Full textRathore, Sandhya, Shambhu Nath Sharma, and Shaival Hemant Nagarsheth. "The Universality of the Kalman Filter." In Advances in Data Mining and Database Management, 277–94. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4706-9.ch011.
Full textRaol, J. R., and N. K. Sinha. "A NONLINEAR FILTER FOR ESTIMATION OF STATES OF A CONTINUOUS-TIME SYSTEM WITH DISCRETE MEASUREMENTS." In Stochastic Control, 43–48. Elsevier, 1987. http://dx.doi.org/10.1016/b978-0-08-033452-3.50011-9.
Full textJovanovic Dolecek, Gordana. "Digital Filters." In Encyclopedia of Multimedia Technology and Networking, Second Edition, 364–72. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-014-1.ch050.
Full textChu, Eleanor. "Applications of the DFT in Digital Filtering and Filters." In Discrete and Continuous Fourier Transforms, 291–302. Chapman and Hall/CRC, 2008. http://dx.doi.org/10.1201/9781420063646-10.
Full textBullock, T. E., and M. J. Moorman. "Extended Kalman Filters 1: Continuous and Discrete Linearizations." In Approximate Kalman Filtering, 3–8. WORLD SCIENTIFIC, 1993. http://dx.doi.org/10.1142/9789814317399_0001.
Full textConference papers on the topic "Continuous-Discrete filter"
Brunke, Lukas, Siqi Zhou, Mingxuan Che, and Angela P. Schoellig. "Practical Considerations for Discrete-Time Implementations of Continuous-Time Control Barrier Function-Based Safety Filters." In 2024 American Control Conference (ACC), 272–78. IEEE, 2024. http://dx.doi.org/10.23919/acc60939.2024.10644713.
Full textXin, Li-Ping, Wen-Yue Shan, Xian-Duo Niu, and Jia-Shuo Liu. "Adaptive fuzzy command filtered discrete control for cascade continuous stirred tank reactors with input constraint." In 2024 43rd Chinese Control Conference (CCC), 721–26. IEEE, 2024. http://dx.doi.org/10.23919/ccc63176.2024.10661604.
Full textYang, Tao, Henk A. P. Blom, and Prashant G. Mehta. "The continuous-discrete time feedback particle filter." In 2014 American Control Conference - ACC 2014. IEEE, 2014. http://dx.doi.org/10.1109/acc.2014.6859259.
Full textAtes, Abdullah, and YangQuan Chen. "Fractional Order Filter Discretization With Marine Predators Algorithm." In ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/detc2021-67611.
Full textLambert, Marc, Silvere Bonnabel, and Francis Bach. "The continuous-discrete variational Kalman filter (CD-VKF)." In 2022 IEEE 61st Conference on Decision and Control (CDC). IEEE, 2022. http://dx.doi.org/10.1109/cdc51059.2022.9992993.
Full textMurata, Masaya, Isao Kawano, and Koichi Inoue. "Ensemble Kalman Filter for Continuous-Discrete State-Space Models." In 2021 60th IEEE Conference on Decision and Control (CDC). IEEE, 2021. http://dx.doi.org/10.1109/cdc45484.2021.9682835.
Full textWang, Tingjun, Haoran Cui, and Xiaoxu Wang. "Variational Compensation Based Nonlinear Filter for Continuous-Discrete Stochastic Systems." In 2020 IEEE 23rd International Conference on Information Fusion (FUSION). IEEE, 2020. http://dx.doi.org/10.23919/fusion45008.2020.9190435.
Full textMiller, Gregory, Alexey Pankov, and Konstantin Siemenikhin. "Minimax filter for statistically uncertain stochastic discrete-continuous linear system." In European Control Conference 2007 (ECC). IEEE, 2007. http://dx.doi.org/10.23919/ecc.2007.7068493.
Full textHerjolfsson, Gisli, Anna Hauksdottir, and Sven Sigurosson. "Closed form Expressions of Linear Continuous-and Discrete-Time Filter Responses." In Proceedings of the 7th Nordic Signal Processing Symposium - NORSIG 2006. IEEE, 2006. http://dx.doi.org/10.1109/norsig.2006.275253.
Full textShin, Vladimir, Du Yong Kim, Georgy Shevlyakov, and Kiseon Kim. "A Suboptimal Filter for Continuous-Discrete Linear Systems with Parametric Uncertainties." In TENCON 2006 - 2006 IEEE Region 10 Conference. IEEE, 2006. http://dx.doi.org/10.1109/tencon.2006.343997.
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