Results 21 to 30 of about 25,371 (266)
Journal of Research of the National Bureau of Standards, 1985 The increased power of small computers makes the use of parameter estimation methods attractive. Such methods have a number of uses in analytical chemistry. When valid models are available, many methods work well, but when models used in the estimation are in error, most methods fail.
Brown, Steven D., Rutan, Sarah C.
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Remote Sensing, 2021 The extended Kalman filter is an extended version of the Kalman filter for a non-linear problem. This study applies this extended Kalman filter to the real-time estimation of the parameters of the dual-pol radar rain rate estimator.
Wooyoung Na, Chulsang Yoo
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IEEE Transactions on Automatic Control, 2009 In this paper, we present a new nonlinear filter for high-dimensional state estimation, which we have named the cubature Kalman filter (CKF). The heart of the CKF is a spherical-radial cubature rule, which makes it possible to numerically compute multivariate moment integrals encountered in the nonlinear Bayesian filter. Specifically, we derive a third-
Ienkaran Arasaratnam, Simon Haykin 0001
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CoRR, 2021 The Kalman filter is a fundamental filtering algorithm that fuses noisy sensory data, a previous state estimate, and a dynamics model to produce a principled estimate of the current state. It assumes, and is optimal for, linear models and white Gaussian noise. Due to its relative simplicity and general effectiveness, the Kalman filter is widely used in
Beren Millidge +3 more
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A review: state estimation based on hybrid models of Kalman filter and neural network
Systems Science & Control Engineering, 2023 In this paper, hybrid models of Kalman filter and neural network for state estimation are reviewed of their corresponding academic achievements, the creation of which is a noteworthy development in state estimation.
Shuo Feng +5 more
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Multiplicative Kalman filtering [PDF]
TEST, 2010 We study a non-linear hidden Markov model, where the process of interest is the absolute value of a discretely observed Ornstein-Uhlenbeck diffusion, which is observed after a multiplicative perturbation. We obtain explicit formulae for the recursive relations which link the relevant conditional distributions.
Comte, Fabienne +2 more
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IET Signal Processing, 2021 One of the current ways to continue space research is to launch ballistic rockets that carry scientific payloads. To improve the accuracy of the instantaneous evolution of the payload impact on the Earths surface, it is necessary to estimate indirect ...
Jose Abreu +2 more
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Improvement of ECG Signal Noise Removal Using Recursive Kalman Filter [PDF]
Journal of Intelligent Procedures in Electrical Technology, 2011 Nowadays, Kalman filter has been wildly used for solving the problem of real world. Kalman filter is a recursive filter that estimates the state of a linear dynamic system from a series of noisy measurements.
Sara Moein, Zahra Beheshti
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Application of H∞ Filter on the Angular Rate Matching in the Transfer Alignment
Discrete Dynamics in Nature and Society, 2016 The transfer alignment (TA) scheme is used for the initial alignment of Inertial Navigation System (INS) on dynamical base. The Kalman filter is often used in TA to improve the precision of TA.
Lijun Song, Zhongxing Duan, Jiwu Sun
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Steady state Kalman filter design for cases and deaths prediction of Covid-19 in Greece
Results in Physics, 2021 In this work we study the applicability of the steady state Kalman filter in order to predict new cases and deaths of Covid-19. We use the actual observations of new cases and deaths. First, we deal with short term prediction, namely daily prediction. We
N. Assimakis +3 more
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