… In this paper, we propose a novel Bayesian framework based on Kalman filter, which does
not … Our method uses a filter bank comprised of two adaptive Kalman filters, one for denoising …

… Here we further improve the Kalman filter algorithm, so that it … filtering method is called
non-adaptive method for short and the fast adaptive algorithm of Kalman filtering is called adaptive …

… adaptive multiuser detector based on Kalman filtering and compares it with previously
published LMS and RLS algorithms for blind adaptive … energy of the Kalman filtering algorithm is …

… are often used in adaptive filtering: Maximum a Posteriori (… these adaptive filters, the
sequential adaptive Kalman filter … be noted that in sequential adaptive filtering the estimation or …

… Kalman filtering results rely heavily on the correct definition of both the mathematical and
stochastic models used in the filtering … , a newly developed adaptive Kalman filter algorithm is …

… that the new adaptive Kalman filter proposed in … Kalman filter (RegularKF), Sage-Husa
adaptive Kalman filter (SageHusaKF), the adaptive Kalman filter only based on genetic algorithm (…

… in substantial estimation errors or even filtering divergence [1]. … The adaptive Kalman filter
(AKF) is the most common method … Smith, “Adaptive Kalman filtering algorithms for integrating …

… An object tracking algorithm using an adaptive Kalman filter (KF) combined with mean shift
(… MS algorithm. The searching result of MS is fed back as the measurement of the adaptive KF…

… Similarly, authors in [8], modeled traffic management using extended Kalman filter. … adaptive
Kalman filter based prediction model is implemented and evaluated. The given algorithm …

… In this paper, an adaptive Kalman filtering algorithm is proposed to solve the estimation
problems when noise statistics are unknown or time varying in an integrated SINS/ DVL system. …