Results 71 to 80 of about 402,870 (201)
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2000 Summary In treating dynamic systems, sequential Monte Carlo methods use discrete samples to represent a complicated probability distribution and use rejection sampling, importance sampling and weighted resampling to complete the on-line ‘filtering’ task. We propose a special sequential Monte Carlo method, the mixture Kalman filter, which
Chen, Rong, Liu, Jun S.
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Kalman filtering and smoothing for linear wave equations with model error [PDF]
, 2011 Filtering is a widely used methodology for the incorporation of observed data into time-evolving systems. It provides an online approach to state estimation inverse problems when data are acquired sequentially.
A M Stuart +5 more
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An Improved Kalman Filtering Method for Indoor Location
, 2016 Indoor real time location technology is widely used in large indoor space, and the location algorithm is the key part of the technology. For the signal interference problems in non-line of sight (NLOS) environment and the deficiency of the existing ...
Guo TT(郭廷廷) +5 more
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Robust Derivative Unscented Kalman Filter Under Non-Gaussian Noise
IEEE Access, 2018 A robust derivative unscented Kalman filter is proposed for a nonlinear system with non-Gaussian noise and outliers based on Huber function. In this paper, the time update process can be performed using a Kalman filter (KF), and measurement update ...
Lijian Yin +4 more
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Support in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general implementations of the Kalman ...
Fernando Tusell
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Kalman filtering for positioning and heading control of ships and offshore rigs
, 2009 In this article, we have described the main components of a ship motion-control system and two particular motion-control problems that require wave filtering, namely, dynamic positioning and heading autopilot.
Fossen, Thor, Perez, Tristan
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Geometry of Kalman Filters [PDF]
, 2012 In this paper is presented a geometric explanation of Kalman filters in terms of a symplectic linear space and a special quadratic form on it. It is an extension of the work of Bougerol with application of a different metric introduced earlier. The author's purpose in this paper is to show that both contraction properties can be understood purely in ...
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Measurement + Control, 2020 In lithium-ion batteries, the accuracy of estimation of the state of charge is a core parameter which will determine the power control accuracy and management reliability of the energy storage systems.
Haotian Shi +5 more
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In this article we present an introduction to various Filtering algorithms and some of their applications to the world of Quantitative Finance. We shall first mention the fundamental case of Gaussian noises where we obtain the well-known Kalman Filter ...
Javaheri, Alireza +2 more
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, 2000 As already pointed out in Hardle, Klinke, and Muller (2000, Chapter 10), state-space models are very useful and flexible in the sense that various recursive methods for time-dependent situations can be formulated as general solutions of filtering, smoothing and prediction problems in state-space models.
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