Results 11 to 20 of about 66,114 (285)
This paper analyzes the performance of Kalman filter-based estimators for robust filtering and rotor asymmetry detection in wound rotor induction machines (WRIMs) using real-time data. Filter models were designed based on an extended model of WRIMs.
Furzana John Basha, Kumar Somasundaram
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Differentially private Kalman filtering [PDF]
9 pages.
Ny, Jerome Le, Pappas, George J.
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41 pages, 9 figures, correction of errors in the general multivariate ...
Sornette, Didier, Ide, Kayo
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Comparative study of state and unknown input estimation for continuous–discrete stochastic systems
Joint state and unknown input estimation for continuous–discrete stochastic systems can be classified into two types: with and without modeling of unknown inputs.
Peng Lu
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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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A New Fusion Estimation Method for Multi-Rate Multi-Sensor Systems With Missing Measurements
A new fusion strategy is introduced in this article to estimate state for multi-rate multi-sensor systems with missing measurements. N sensors, which possess various sampling rates, render the measurements. Missing measurements with a certain probability
Mojtaba Kordestani +3 more
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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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Joint semi-blind detection and channel estimation in space-frequency trellis coded MIMO-OFDM [PDF]
This paper considers an OFDM system with a multiple-input multiple-output (MIMO) configuration, which uses space-frequency trellis coding (SFTC). A novel method of decoding SFTC without a need to transmit separate training sequences is developed.
McGeehan, JP, Nix, AR, Piechocki, RJ
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The existing adaptive Kalman filters for tracking manoeuvring targets by wireless sensor networks can easily lose robustness when both the measurement and process noises are unknown and time‐varying, resulting in large positioning errors.
Xuming Fang, Dandan Huang
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A New Strategy for Combining Nonlinear Kalman Filters With Smooth Variable Structure Filters
Bayesian filters exemplified by the celebrated Kalman Filter (KF), and its non-linear variants rely on a fairly accurate state-space model of the system under study.
Salman Akhtar +3 more
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