The new feature of this paper is that the derivation of the optimal smoothing estimator is based only on the Wiener-Hopf theory. Using the Wiener-Hopf equations ...
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This paper, by combining the robust recursive least-squares (RLS) Wiener filter and the RLS Wiener fixed-lag smoothing algorithm, proposes the robust RLS Wiener ...
Oct 30, 2022 · Abstract. A robust fixed-lag smoothing approach is proposed in the case there is a mismatch between the nominal model and the actual model.
The linear fixed-lag Kalman smoother algorithm of CST94 consists of the Kalman filter equations (1)-(2) along with a set of equations appended to those of ...
The filter is named after Rudolf E. Kálmán. The Kalman filter keeps track of the estimated state of the system and the variance or uncertainty of the estimate.
Abstract The fixed-interval smoothing estimator for a linear distributed parameter system with a noisy observation at discrete points on the spatial domain ...
The two main formulations of smoothing are tackled here: the joint estimation problem. (fixed lag or fixed interval), where the probability of a series of ...
This paper presents recursive least-squares (RLS) estimation algorithms using the covariance information in linear discrete-time distributed parameter systems.
Fixed interval smoothing algorithm is developed using a backward sweep. It is found that the smoothing estimates are independent of their error covariances.
The two-filter smoother gives the smoothed estimate as a combination of a forward and a backward estimate. Both estimates come from Kalman filters. A surprising ...