… observation measurements are lost in a random fashion. We formulate the Kalman filtering
problem with partial observation … Thus, we have a condition in terms of the function gλ1λ2 (X) …

… the observation process. The paper shows that the sufficient conditions for the Kalman Filter
to … More recently, Wang and Guo [3] provide sufficient conditions on the stochastic Grammian …

… We show that under a weak distributed detectability condition: 1) the GIKF error process …
we impose the following weak assumptions on the signal/observation model: Stabilizability: …

… First we examine our approach in the Lorenz-96 model, a low-order model where only one
type of observation is available. The results show that the estimation of inflation alone does …

… condition at 0 h (at a time when observations yo 0 were assimilated) and that from initial
condition … in detecting poor observations than the monitoring of observational increments. In this …

… condition for stability of the Kalman filter. This condition is used to find necessary and sufficient
conditions … In this work, low-complexity realisations have been a focus of attention [6], and …

… and continuity) from the constrained Kalman filter are significantly superior to those from
the conventional Kalman filter, particularly under extremely poor observation conditions. …

… The ensemble Kalman filter (EnKF) uses an ensemble of … experiments using simulated
observations of radial velocity … the radar observations. Assimilation of simulated radial-velocity …

… Kalman filters focuses on sensor networks monitoring low dimension systems. This research
replicates an th-order Kalman filter … initial conditions, a local filter step (including observation …

… density function satisfying the usual conditions which describes the … is poor at distinguishing
between target types and so sensor 2 information is used for this purpose. If now we observe …