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- W2095376999 abstract "This article considers the application of variational Bayesian methods to joint recursive estimation of the dynamic state and the time-varying measurement noise parameters in linear state space models. The proposed adaptive Kalman filtering method is based on forming a separable variational approximation to the joint posterior distribution of states and noise parameters on each time step separately. The result is a recursive algorithm, where on each step the state is estimated with Kalman filter and the sufficient statistics of the noise variances are estimated with a fixed-point iteration. The performance of the algorithm is demonstrated with simulated data." @default.
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- W2095376999 date "2009-03-01" @default.
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- W2095376999 title "Recursive Noise Adaptive Kalman Filtering by Variational Bayesian Approximations" @default.
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- W2095376999 doi "https://doi.org/10.1109/tac.2008.2008348" @default.
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