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Journal articles on the topic 'Continuous-Discrete filter'

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Published: 5 October 2024

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1

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.

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2

Lange, 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.

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Abstract We provide a rigorous derivation of the ensemble Kalman–Bucy filter as well as the ensemble transform Kalman–Bucy filter in case of nonlinear, unbounded model and observation operators. We identify them as the continuous time limit of the discrete-time ensemble Kalman filter and the ensemble square root filters, respectively, together with concrete convergence rates in terms of the discretisation step size. Simultaneously, we establish well-posedness as well as accuracy of both the continuous-time and the discrete-time filtering algorithms.

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3

Sharma, 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.

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4

Hu, 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.

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The model of bearings-only tracking is generally described by discrete–discrete filtering systems. Discrete robust methods are also frequently used to address measurement uncertainty problems in bearings-only tracking. The recently popular continuous–discrete filtering system considers the state model of the target to be continuous in time, and is more suitable for bearings-only tracking because of its higher mathematical solution accuracy. However, the sufficient evaluation of robust methods in continuous–discrete systems is not available. In addition, in the different continuous–discrete measurement environments, the choice of a robust algorithm also needs to be discussed. To fill this gap, this paper firstly establishes the continuous–discrete target tracking model, and then evaluates the performance of proposed robust square-root continuous–discrete cubature Kalman filter algorithms in the measurement of uncertainty problems. From the simulation results, the robust square-root continuous–discrete maximum correntropy cubature Kalman filter algorithm and the variational Bayesian square-root continuous–discrete cubature Kalman filter algorithm have better environmental adaptability, which provides a promising means for solving continuous–discrete robust problems.

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5

Murata, 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.

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6

Knudsen, 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.

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7

Chubich, 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.

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Introduction: usually there are some outliers (abnormal measurements) in observed data, and they can significantly affect the quality of the data processing. Many dynamic processes are described with stochastic nonlinear equations. Modern nonlinear filters that include the cubature Kalman filter, which deserves a special attention, cannot effectively process data containing abnormal measurements. One of the possible solutions to this problem is to use so-called robust methods that have good performance when one has to analyze data containing outliers. The paper deals with the common situations, when the considered process is actually continuous, but the observed data is taken discretely. Purpose: identifying the most effective advanced robust modifications of the continuous-discrete cubature Kalman filter and giving the appropriate recommendations for their appliance. Results: four modifications of the continuous-discrete cubature Kalman filter have been proposed based on the variational Bayesian and correntropy robust approaches to parameter estimation for stochastic processes. All the modifications have parameters with optimal values depending on both the selected mathematical model and the considered set of observations composing the sample. These values are determined numerically by minimizing the accumulated root mean square error on some grid. The research on the effectiveness of the proposed robust modifications has been carried out for the problem of tracking a space vehicle during its reentry into the atmosphere. The stochastic and the grouped outliers have been considered. Two most effective filters that have approximately equal qualities of estimation have been derived. The correntropy filter that has one configurable parameter can be recommended for practical using.

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8

Rudenko, 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.

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9

Weller, 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.

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10

Shald, 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.

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11

Jwo, Dah-Jing, and Amita Biswal. "Implementation and Performance Analysis of Kalman Filters with Consistency Validation." Mathematics 11, no. 3 (January 18, 2023): 521. http://dx.doi.org/10.3390/math11030521.

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This paper provides a useful supplement note for implementing the Kalman filters. The material presented in this work points out several significant highlights with emphasis on performance evaluation and consistency validation between the discrete Kalman filter (DKF) and the continuous Kalman filter (CKF). Several important issues are delivered through comprehensive exposition accompanied by supporting examples, both qualitatively and quantitatively for implementing the Kalman filter algorithms. The lesson learned assists the readers to capture the basic principles of the topic and enables the readers to better interpret the theory, understand the algorithms, and correctly implement the computer codes for further study on the theory and applications of the topic. A wide spectrum of content is covered from theoretical to implementation aspects, where the DKF and CKF along with the theoretical error covariance check based on Riccati and Lyapunov equations are involved. Consistency check of performance between discrete and continuous Kalman filters enables readers to assure correctness on implementing and coding for the algorithm. The tutorial-based exposition presented in this article involves the materials from a practical usage perspective that can provide profound insights into the topic with an appropriate understanding of the stochastic process and system theory.

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12

Bäuerle, Nicole, Igor Gilitschenski, and Uwe Hanebeck. "Exact and approximate hidden Markov chain filters based on discrete observations." Statistics & Risk Modeling 32, no. 3-4 (December 1, 2015): 159–76. http://dx.doi.org/10.1515/strm-2015-0004.

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Abstract We consider a Hidden Markov Model (HMM) where the integrated continuous-time Markov chain can be observed at discrete time points perturbed by a Brownian motion. The aim is to derive a filter for the underlying continuous-time Markov chain. The recursion formula for the discrete-time filter is easy to derive, however involves densities which are very hard to obtain. In this paper we derive exact formulas for the necessary densities in the case the state space of the HMM consists of two elements only. This is done by relating the underlying integrated continuous-time Markov chain to the so-called asymmetric telegraph process and by using recent results on this process. In case the state space consists of more than two elements we present three different ways to approximate the densities for the filter. The first approach is based on the continuous filter problem. The second approach is to derive a PDE for the densities and solve it numerically. The third approach is a crude discrete time approximation of the Markov chain. All three approaches are compared in a numerical study.

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13

Santos‐Díaz, Eduardo, Simon Haykin, and Thomas R. Hurd. "Fifth‐degree continuous–discrete cubature Kalman filter for radar." IET Radar, Sonar & Navigation 12, no. 11 (November 2018): 1225–32. http://dx.doi.org/10.1049/iet-rsn.2018.5148.

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14

Duan, Zhaoxia, Jinling Liang, and Zhengrong Xiang. "Filter design for continuous-discrete Takagi-Sugeno fuzzy system with finite frequency specifications." Mathematical Modelling and Control 3, no. 4 (2023): 387–99. http://dx.doi.org/10.3934/mmc.2023031.

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<abstract><p>This paper was concerned with the problem of filter design for the continuous-discrete system in the Takagi-Sugeno (T-S) fuzzy model. In a known finite frequency (FF) domain, an FF $ H_\infty $ performance was defined for the nonlinear continuous-discrete system. With the designed filter, sufficient conditions were then established for the filtering error system to be asymptotically stable and having a prescribed FF $ H_\infty $ performance. After that, a systematic method for the filter design was proposed. Finally, an example was provided to check effectiveness of the derived results.</p></abstract>

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15

NIELSEN, JAN NYGAARD, and MARTIN VESTERGAARD. "ESTIMATION IN CONTINUOUS-TIME STOCHASTIC VOLATILITY MODELS USING NONLINEAR FILTERS." International Journal of Theoretical and Applied Finance 03, no. 02 (April 2000): 279–308. http://dx.doi.org/10.1142/s0219024900000139.

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The stylized facts of stock prices, interest and exchange rates have led econometricians to propose stochastic volatility models in both discrete and continuous time. However, the volatility as a measure of economic uncertainty is not directly observable in the financial markets. The objective of the continuous-discrete filtering problem considered here is to obtain estimates of the stock price and, in particular, the volatility using discrete-time observations of the stock price. Furthermore, the nonlinear filter acts as an important part of a proposed method for maximum likelihood for estimating embedded parameters in stochastic differential equations. In general, only approximate solutions to the continuous-discrete filtering problem exist in the form of a set of ordinary differential equations for the mean and covariance of the state variables. In the present paper the small-sample properties of a second order filter is examined for some bivariate stochastic volatility models and the new combined parameter and state estimation method is applied to US stock market data.

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16

Cui, Li Hong, Yan Zhou, Bin Huang, and Jian Jun Sun. "Moments and Parametrizing Construction for 3-Band Biorthogonal Scaling Coefficients." Applied Mechanics and Materials 284-287 (January 2013): 3189–93. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3189.

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Regensburger and Scherzer described a symbolic computation method for moments and filter coefficients of scaling functions and obtained parametrizing compactly supported orthonormal wavelets. Following the idea, we are devoted to a study moments and parameterization construction for 3-band biorthogonal scaling coefficients with several vanishing moments. Firstly, we investigate the relations between filter lengths and symmetry. Then, we prove the relationship between dual continuous moments of 3-band biorthogonal scaling functions in theorem 2. This theorem reveals that the sum of continuous moments of dual scaling functions and is completely determined by the lower discrete moments. And we show the fact that the odd-indexed discrete moments are determined by the smaller even-indexed discrete moments. Finally, a family 3-band biorthogonal scaling coefficients with discrete moments as parameters are explicitly expressed based on computer algebra.

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17

Patel, Zubeida, and Edward Boje. "A Hybrid, Coupled Approach to the Continuous-Discrete Kalman Filter." IEEE Control Systems Letters 5, no. 3 (July 2021): 827–32. http://dx.doi.org/10.1109/lcsys.2020.3005329.

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18

Frogerais, P., Jean-Jacques Bellanger, and L. Senhadji. "Various Ways to Compute the Continuous-Discrete Extended Kalman Filter." IEEE Transactions on Automatic Control 57, no. 4 (April 2012): 1000–1004. http://dx.doi.org/10.1109/tac.2011.2168129.

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19

Kulikov, Gennady Yu, and Maria V. Kulikova. "Accurate Numerical Implementation of the Continuous-Discrete Extended Kalman Filter." IEEE Transactions on Automatic Control 59, no. 1 (January 2014): 273–79. http://dx.doi.org/10.1109/tac.2013.2272136.

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20

Wang, Jiaolong, Jihe Wang, Dexin Zhang, and Xiaowei Shao. "Stochastic Feedback Based Kalman Filter for Nonlinear Continuous-Discrete Systems." IEEE Transactions on Automatic Control 63, no. 9 (September 2018): 3002–9. http://dx.doi.org/10.1109/tac.2017.2776604.

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21

Niu, Yifeng, Yirui Cong, and Lizhen Wu. "Event-Triggered Continuous-Discrete Kalman Filter With Controllable Estimation Error." IEEE Access 6 (2018): 42482–96. http://dx.doi.org/10.1109/access.2018.2860626.

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22

Kulikov, Gennady Yu, and Maria V. Kulikova. "The Accurate Continuous-Discrete Extended Kalman Filter for Radar Tracking." IEEE Transactions on Signal Processing 64, no. 4 (February 2016): 948–58. http://dx.doi.org/10.1109/tsp.2015.2493985.

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23

Mao, Hongquan. "Advancements in Filter Technology: Evolution and Applications." Highlights in Science, Engineering and Technology 97 (May 28, 2024): 112–16. http://dx.doi.org/10.54097/603hn182.

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This paper explores the historical trajectory and contemporary applications of signal processing filters. From the early days of analog filters to the current digital era, the paper traces their evolution, emphasizing key developments in active RC filters, monolithic integrated op amps, and the transition to switched-capacitor and continuous-time filters. Fundamentals of analog and digital filters are outlined, distinguishing their processing of continuous-time and discrete-time signals. The classification of filters, including low-pass, high-pass, band-pass, and band-stop, is discussed with insights into their specific applications. The paper delves into crucial applications in audio processing, video processing, communication systems, power management, and sensor signal processing, showcasing filters' pivotal role in enhancing signal quality across diverse fields. Addressing emerging technologies, the paper highlights adaptive and deep learning filters, projecting the future trends in filter technology. It anticipates developments in analog integrated filters, emphasizing the growing significance of integrated circuits technology. This comprehensive review aims to deepen readers' understanding and inspire continued innovation in signal processing.

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24

Reddy, Anugu Sumith, and Amit Apte. "Stability of non-linear filter for deterministic dynamics." Foundations of Data Science 3, no. 3 (2021): 647. http://dx.doi.org/10.3934/fods.2021025.

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<p style='text-indent:20px;'>This papers shows that nonlinear filter in the case of deterministic dynamics is stable with respect to the initial conditions under the conditions that observations are sufficiently rich, both in the context of continuous and discrete time filters. Earlier works on the stability of the nonlinear filters are in the context of stochastic dynamics and assume conditions like compact state space or time independent observation model, whereas we prove filter stability for deterministic dynamics with more general assumptions on the state space and observation process. We give several examples of systems that satisfy these assumptions. We also show that the asymptotic structure of the filtering distribution is related to the dynamical properties of the signal.</p>

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25

Чубич, Владимир Михайлович, and Светлана Олеговна Кулабухова. "Square-root algorithms for robust modifications of the continuous-discrete cubature Kalman filter." Вычислительные технологии, no. 3 (July 15, 2020): 88–98. http://dx.doi.org/10.25743/ict.2020.25.3.010.

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Предложены две устойчивые к ошибкам машинного округления и к аномальным данным квадратно-корневые модификации непрерывно-дискретного кубатурного фильтра Калмана, основанные на вариационном байесовском и коррентропийном подходах. Апробация разработанных алгоритмов на модельной задаче со случайным характером расположения аномальных наблюдений показала их работоспособность при сопоставимом качестве фильтрации. Подтверждена алгебраическая эквивалентность представленных квадратно-корневых и стандартных версий Rounding errors due to the finite length of machine word can significantly affect the quality of estimation and filtering when solving the corresponding problems in various subject areas. In this regard, to improve the reliability of the obtained results, it is advisable to develop and then apply square-root modifications of the used algorithms. Purpose: developing the square-root modifications of the continuous-discrete cubature Kalman filter on the basis of variational Bayesian and correntropy approaches. Methodology: matrix orthogonal QR decomposition. Findings: two robust (resistant to the possible presence of anomalous data and to machine rounding errors) modifications of the continuous-discrete cubature Kalman filter have been developed. The first (variational Bayesian) algorithm is obtained by extending the known discrete equations of the extrapolation stage to the continuous-discrete case. The second algorithm, based on the maximum correntropy criterion, is proposed in this paper for the first time. The developed square-root algorithms for nonlinear filtering are validated on the example of one stochastic dynamical system model with the random location of anomalous observations. In doing so, the filtering quality, estimated by the value of the accumulated mean square error, was quite comparable for both modifications during equivalent results obtained for the corresponding root-free analogues. Value: the proposed square-root versions of robust modifications of the continuous-discrete cubature Kalman filter are algebraically equivalent to their standard analogues. Meanwhile, positive definiteness and symmetry of covariance matrices of the state vector estimates at the extrapolation and the filtration stages are provided. The developed algorithms will be used to develop software and mathematical support for parametric identification of stochastic nonlinear continuous-discrete systems in the presence of anomalous observations in the measurement data

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26

Moireau, P. "A discrete-time optimal filtering approach for non-linear systems as a stable discretization of the Mortensen observer." ESAIM: Control, Optimisation and Calculus of Variations 24, no. 4 (October 2018): 1815–47. http://dx.doi.org/10.1051/cocv/2017077.

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In this work, we seek exact formulations of the optimal estimator and filter for a non-linear framework, as the Kalman filter is for a linear framework. The solution is well established with the Mortensen filter in a continuous-time setting, but we seek here its counterpart in a discrete-time context. We demonstrate that it is possible to pursue at the discrete-time level an exact dynamic programming strategy and we find an optimal estimator combining a prediction step using the model and a correction step using the data. This optimal estimator reduces to the discrete-time Kalman estimator when the operators are in fact linear. Furthermore, the strategy that consists of discretizing the least square criterion and then finding the exact estimator at the discrete level allows to determine a new time-scheme for the Mortensen filter which is proven to be consistent and unconditionally stable, with also a consistent and stable discretization of the underlying Hamilton-Jacobi-Bellman equation.

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27

Jimenez, Juan Carlos. "Approximate linear minimum variance filters for continuous-discrete state space models: convergence and practical adaptive algorithms." IMA Journal of Mathematical Control and Information 36, no. 2 (November 16, 2017): 341–78. http://dx.doi.org/10.1093/imamci/dnx047.

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Abstract In this article, approximate linear minimum variance (LMV) filters for continuous-discrete state space models are introduced. The filters are derived from a wide class of recursive approximations to the predictions for the first two conditional moments of the state equation between each pair of consecutive observations. The convergence of the approximate filters to the exact LMV filter is proved when the error between the predictions and their approximations decreases no matter the time distance between observations. As particular instance, the order-$\beta$ local linearization filters are presented and expounded in detail. Practical adaptive algorithms are also provided and their performance in simulation is illustrated with various examples. The proposed filters are intended for the recurrent practical situation where a stochastic dynamical system should be identified from a reduced number of partial and noisy observations distant in time.

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28

REZAI-RAD, GHOLAMALI, and AHMAD CHELDAVI. "DISCRETE TIME-DOMAIN ANALYSIS OF NONUNIFORM LOSSLESS COUPLED TRANSMISSION LINES." Journal of Circuits, Systems and Computers 14, no. 05 (October 2005): 973–86. http://dx.doi.org/10.1142/s0218126605002763.

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In this paper, a discrete time-domain method to analyze multiple coupled nonuniform lossless transmission lines has been presented. The solution is based on the steplines approximation of the nonuniform transmission lines and quasi-TEM assumptions. Using steplines approximation, the system of coupled nonuniform transmission lines is decomposed into a large number of coupled steplines with different characteristics. Then, using modal decomposition method, the system of coupled partial differential equations for each step is decomposed to a set of uncoupled ordinary wave equation. Using time-domain approach and invoking the boundary condition at the discontinuities of the adjacent steps, each step is modeled as continuous time linear filter characterized by a time-domain transfer matrix. Finally, this continuous time linear filter (for band limited input signal), is modeled as a discrete time-domain linear filter with constant matrix coefficients using sampling theorem. The method proposed here can be implemented using general purpose software packages like MATLAB.

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29

Li, Linmin, Peng Lin, and Junfeng Zhang. "Event-Triggered Asynchronous Filter of Positive Switched Systems with State Saturation." Mathematical Problems in Engineering 2022 (June 21, 2022): 1–24. http://dx.doi.org/10.1155/2022/7276646.

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This paper investigates the event-triggered asynchronous filter of positive switched systems with state saturation using linear programming and multiple Lyapunov functions. First, a filter is constructed for continuous-time positive switched systems. Under the asynchronous switching law, an error system is proposed with respect to positive switched systems and their filters, where the state saturation term is described in a polytopic form by virtue of the saturation property. A novel event-triggering condition is addressed based on a 1-norm inequality. Under the event-triggering condition, the error system is transformed into an interval system with lower and upper bounds. By using multiple Lyapunov functions and linear programming, the positivity and stability of the error system are achieved by considering the corresponding properties of the lower and upper bounds, respectively. Then, the event-triggered l1-gain filter and nonfragile filter are also proposed for the systems with disturbances. Moreover, the presented filter framework is extended to the discrete-time case. Finally, two examples are given to verify the effectiveness of the proposed filters.

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30

Zhang, Zhiqiang, Zhongle Liu, and Hongxin Zhang. "Underwater mobile gravity measurement data processing using continuous-discrete Kalman filter." AIP Advances 11, no. 8 (August 1, 2021): 085104. http://dx.doi.org/10.1063/5.0054053.

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31

Cacace, Filippo, Valerio Cusimano, Alfredo Germani, Pasquale Palumbo, and Marco Papi. "Optimal Continuous-Discrete Linear Filter and Moment Equations for Nonlinear Diffusions." IEEE Transactions on Automatic Control 65, no. 10 (October 2020): 3961–76. http://dx.doi.org/10.1109/tac.2019.2953456.

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32

Kulikov, Gennady Yu, and Maria V. Kulikova. "High-order accurate continuous-discrete extended Kalman filter for chemical engineering." European Journal of Control 21 (January 2015): 14–26. http://dx.doi.org/10.1016/j.ejcon.2014.11.003.

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33

Liu, Bin. "Ensemble unscented Kalman filter for state inference in continuous–discrete systems." Journal of Engineering 2014, no. 5 (May 1, 2014): 234–37. http://dx.doi.org/10.1049/joe.2014.0076.

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34

Garcia-Fernandez, Angel F., and Simon Maskell. "Continuous-Discrete Multiple Target Filtering: PMBM, PHD and CPHD Filter Implementations." IEEE Transactions on Signal Processing 68 (2020): 1300–1314. http://dx.doi.org/10.1109/tsp.2020.2968247.

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35

Aalto, Atte. "Convergence of discrete-time Kalman filter estimate to continuous time estimate." International Journal of Control 89, no. 4 (October 4, 2015): 668–79. http://dx.doi.org/10.1080/00207179.2015.1090017.

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36

Tempe, Smita Vasant. "A Review on Image Denoising Techniques." International Journal for Research in Applied Science and Engineering Technology 9, no. 12 (December 31, 2021): 761–64. http://dx.doi.org/10.22214/ijraset.2021.39342.

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Abstract: The goal of this study is to find a "genuine" two-dimensional transform that can capture the fundamental geometrical structure that is important in visual information. The discontinuous character of the data is the most difficult aspect of analysing geometry in photographs. Unlike previous approaches, such as curvelets, which generate a transform in the continuous domain and then discretize for sampled data, we begin with a discrete-domain construction and then investigate its convergence to a continuous-domain expansion. We use nonseparable filter banks to create a discrete-domain multiresolution and multidirection expansion, similar to how wavelets are produced from filter banks. As a result of this construction, a flexible multiresolution, local, and directed picture expansion employing contour segments is obtained, and it is therefore useful.

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Ye, Hongling, Ning Chen, Yunkang Sui, and Jun Tie. "Three-Dimensional Dynamic Topology Optimization with Frequency Constraints Using Composite Exponential Function and ICM Method." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/491084.

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The dynamic topology optimization of three-dimensional continuum structures subject to frequency constraints is investigated using Independent Continuous Mapping (ICM) design variable fields. The composite exponential function (CEF) is selected to be a filter function which recognizes the design variables and to implement the changing process of design variables from “discrete” to “continuous” and back to “discrete.” Explicit formulations of frequency constraints are given based on filter functions, first-order Taylor series expansion. And an improved optimal model is formulated using CEF and the explicit frequency constraints. Dual sequential quadratic programming (DSQP) algorithm is used to solve the optimal model. The program is developed on the platform of MSC Patran & Nastran. Finally, numerical examples are given to demonstrate the validity and applicability of the proposed method.

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38

Rashmi, Ruchi, and Shweta Jagtap. "A comparative study of phase margin based digital and analog controlled synchronous buck with optimum LC filter." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 38, no. 6 (October 24, 2019): 2020–39. http://dx.doi.org/10.1108/compel-12-2018-0508.

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Purpose Traditionally, industrial power supplies have been exclusively controlled through analog control to sustain high reliability with low cost. However, with the perpetual decrement in cost of digital controllers, the feasibility of a digitally controlled switch mode power supply has elevated significantly. This paper aims to outline the challenges related to the design of digital proportional-integral (PI) controlled synchronous rectifier (SR) buck converter by comparing controller performance in continuous and discrete time. The trapezoidal approximation-based digital PI control is designed for low voltage and high-frequency SR buck converter operating under continuous conduction mode. Design/methodology/approach The analog and digital controller are designed using a SISO tool of MATLAB. Here, zero-order hold transform is used to convert the transfer function from continuous to discrete time. Frequency and time domain analysis of continuous plant, discrete plant and close loop system is performed. The designed digital PI control is simulated in MATLAB Simulink. The simulated results is also verified on hardware designed around digital signal processing control. Findings The continuous and discrete control loops are validated with multiple tests in the time and frequency domain. The detailed steady state theoretical analysis and performance of the SR buck converter is presented and verified by simulation. It is found that the delay in digital control loop results in a low phase margin. This phase margin decreases with higher bandwidth. The hardware experiments with the digital control loop are carried out on a 10 W prototype. The chosen parameters for the SR buck converter are found to be optimum for steady and transient state response. Originality/value This paper compares the digital and analog control approach of compensator design. It focuses on the implications created at the time of transforming the control design from continuous to discrete time. Further, it also focuses on the selection of parameters such as phase margin, bandwidth and low pass filter.

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39

Sharroush, Sherif, and Yasser Abdalla. "A Real-Time Electronically Tunable All-MOS Universal Biquadratic Voltage-Mode Filter." Jordan Journal of Electrical Engineering 9, no. 2 (2023): 242. http://dx.doi.org/10.5455/jjee.204-1671142029.

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— In this paper, an electronically tunable universal biquadratic voltage-mode filter that is based only on MOS transistors is proposed. Configuration of the proposed filter is simple and there is no need to use component matching. Since the proposed filter contains only MOS transistors, it is very suitable for implementation in system-on-chip (SoC) applications. The cutoff frequency of the lowpass (LP) and highpass (HP) filters as well as the center frequency and the bandwidth of the bandpass (BP) and bandstop (BS) filters can be controlled either in a continuous range or in a discrete manner by means of a digital control word. Besides, the filter type can be changed during the real time by an appropriate code. Operation of all the filtering functions are verified by simulation using the Berkeley predictive-technology models (BPTM) of the 130 nm complementary metal-oxide semiconductor (CMOS) technology with power-supply voltage, VDD, of 1.2 V. The proposed filter is analyzed quantitatively, and the effects of the total-harmonic distortion (THD), noise, process, voltage and temperature (PVT) variations are also investigated. The average power consumption of the LP, HP, BP, BS, and allpass (AP) filters are found to be 30, 118, 74, 118, and 30 (all in µW). The price paid for all these advantages is more sensitivity to process variations for the lowpass filter.

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Lian, Jing, Lin Hui Li, Xiao Yong Shen, and Xian Peng Hao. "Multi-Scale Edge Extraction Based Stereo Matching Algorithm." Applied Mechanics and Materials 44-47 (December 2010): 4162–66. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.4162.

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In the field of robot vision, edge feature based stereo matching algorithm can reconstruct the targets with clear contours, which needs accurate and continuous target edges been extracted. In the paper, the smoothing filter operator was designed based on the discrete criteria of edge extraction and its correspondence optimal linear filter. Edge extraction was carried out incorporated the nonmaximum suppression and two thresholds techniques. The discrete criteria based multi-scale edge extraction method was studied with full use of the multi-scale character of the edge information. The detected multi-scale edges were synthesized to obtain the accurate and continuous single pixel wide edge. Then an edge feature based stereo matching algorithm was proposed to obtain 3D information of target. The experimental results demonstrate that the method can effectively suppress disturbance in outdoor environment and reconstruct target contour clearly.

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Belonogov, Viktor. "Operational Adaptation of Digital Filter Parameters when Changing the Discrete Time Step in the Problems of Forming the Control of Unmanned Vehicles Using Satellite Measurements." E3S Web of Conferences 446 (2023): 05004. http://dx.doi.org/10.1051/e3sconf/202344605004.

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For the tasks of controlling unmanned vehicles using external information signals, in some cases, a change in the time parameters T0 of periodic data receipt is typical. Such systems, the processing of incoming information in order to form digital control is implemented by digital filters (DF), based on discrete samples x[k] of some continuous signal x(t) at quantization times tk=k*T0 Here T0[seconds]- the period of discreteness in time, k=0,1,2,.. an integer variable, essentially a time counter. The properties of the filter are uniquely specified by its specific mathematical model - the discrete impulse transient function [1,3] of the filter (DITF), which characterizes the filter operation at a specific step T0= 1/f0, where f0 (hertz) is the frequency. When the time intervals T0 of data arrival change, for example, due to a change in the transmission conditions in the radio channel, or due to a change in the location of the satellite constellation, the filter properties will change during operation [2], and if T0 changes significantly, such filtering can lead to unsatisfactory results. In this paper, for the parameters of the digital filter, the adaptation problem is posed and solved, which ensures the invariance of the nature DITF, in contrast to the stabilization of the frequency properties of the digital filter, studied in [4]. To rebuild the numerical parameters of the filter, an algorithm is proposed that uses information about the time intervals obtained by direct measurement. At the stage of filter development, a special recalculation matrix is formed and when the filter is running in real time, the digital filter parameters are recalculated. For a model example, the calculation results are presented, which show good tuning accuracy, stable filter characteristics, as well as the simplicity of the required calculations on board with a significant change in time intervals.

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Stoica, Adrian Mihail. "A New Kalman-Type Approach for Satellites Attitude Determination." Applied Mechanics and Materials 555 (June 2014): 57–65. http://dx.doi.org/10.4028/www.scientific.net/amm.555.57.

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This paper presents a Kalman type method for attitude determination of satellites. It is shown that the linearized model describing the satellite kinematics may be expressed as a stochastic system corrupted with both additive and multiplicative white noise. For this class of stochastic models a hybrid Kalman filter is used to estimate the quaternion expressing the satellite attitude and the bias of the inertial measurement unit. By contrast with the classical Kalman filters, the hybrid filter used in this paper includes a continuous-time and a discrete-time component. The advantage is that it may provide a time varying estimation of the states between the sampling moments which usually are sparse in space applications. The theoretical developments is illustrated via a numerical case study.

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Detkov, A. N. "Optimal Discrete Estimation of Reference Points of a Discrete-Continuous Markov Process against the Background of Correlated Markov Noise." Радиотехника и электроника 68, no. 7 (July 1, 2023): 650–59. http://dx.doi.org/10.31857/s0033849423060025.

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In this paper, we solve the problem of synthesizing optimal and quasi-optimal algorithms for estimating the reference points of continuous components of a vector discrete-continuous Markov random process with allowance for the known statistical characteristics of additive Markovian correlated noise using the methods of the Markov theory of estimation of random processes. The method of difference measurements was used while synthesizing the algorithms. A block diagram of a quasi-optimal digital filter is given. Using a simple example, simulation shows the performance of a quasi-optimal algorithm in statistically uncertain situations.

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Wang, Ningyuan, and Daniel B. Forger. "The Level Set Kalman Filter for State Estimation of Continuous-Discrete Systems." IEEE Transactions on Signal Processing 70 (2022): 631–42. http://dx.doi.org/10.1109/tsp.2021.3133698.

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Ishihara, Shinji, and Masaki Yamakita. "Continuous-Discrete Robust Extended Kalman Filter for Nonlinear Systems with Parameter Uncertainties." Transactions of the Institute of Systems, Control and Information Engineers 29, no. 7 (2016): 302–10. http://dx.doi.org/10.5687/iscie.29.302.

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Singer, Hermann. "Continuous-discrete state-space modeling of panel data with nonlinear filter algorithms." AStA Advances in Statistical Analysis 95, no. 4 (October 20, 2011): 375–413. http://dx.doi.org/10.1007/s10182-011-0172-3.

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Feddaoui, Aïda, Nicolas Boizot, Eric Busvelle, and Vincent Hugel. "High-gain extended Kalman filter for continuous-discrete systems with asynchronous measurements." International Journal of Control 93, no. 8 (November 1, 2018): 2001–14. http://dx.doi.org/10.1080/00207179.2018.1539525.

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Gajic, Z., and J. Boka. "Kalman Filtering Error Due to Inaccuracy in Filter’s Initial Condition." Journal of Dynamic Systems, Measurement, and Control 119, no. 1 (March 1, 1997): 119–22. http://dx.doi.org/10.1115/1.2801202.

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It is a very well known fact that the initial condition of the optimal linear Kalman filter has to be set at the mean value of the system initial state. In this paper, we have derived an expression for the filtering error in the case when this condition is not satisfied. Both continuous- and discrete-time domain filters are considered. The obtained results are simple and elegant and clearly indicate the effect of the erroneous filter’s initial condition. An example is included in order to demonstrate the results obtained.

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Belonogov, Viktor D. "Reconstruction of digital filter parameters when changing the data arrival period." Revista Amazonia Investiga 11, no. 50 (March 10, 2022): 161–69. http://dx.doi.org/10.34069/ai/2022.50.02.16.

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We consider the problem of forming an algorithm for the operation of a digital filter that provides processing, according to a certain law, of discrete samples x[k] of some continuous signal x(t) at the moments of quantization tк=k ∙T0, where T0 -[second]- is the discreteness period in time, and k=0,1,2,.. is the integer variable defining dimensionless discrete time. This work poses and solves the problem of forming the digital filter parameters restructuring, which ensures that the filtering properties remain unchanged when the frequency of information is changed, in particular, the constancy of the frequency and pseudo-frequency characteristics of the filter. An algorithm for restructuring the numerical parameters of the filter based on information about the time intervals of information arrival has been developed. At the stage of filter development, a special conversion matrix is formed for the specified parameters, and at the stage of filter operation in real time, an operational recalculation of the digital filter parameters is performed. For the test example, the calculation results are given, showing good tuning accuracy and stable filter characteristics with a significant change in the quantization frequency.

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Chigansky, P., R. Liptser, and B. Z. Bobrovsky. "A simple asymptotically optimal filter over an infinite horizon." Journal of Applied Mathematics and Stochastic Analysis 14, no. 1 (January 1, 2001): 93–112. http://dx.doi.org/10.1155/s1048953301000089.

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A filtering problem over an infinite horizon for a continuous time signal and discrete time observation in the presence of non-Gaussian white noise is considered. Conditions are presented, under which a nonlinear Kalman type filter with limiter is asymptotically optimal in the mean square sense for long time intervals given provided the sampling frequency is sufficiently high.

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