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The reduced rank square root filter is a special formulation of the Kalman filter for assimilation of data in large scale models that represent simple linear or complex nonlinear systems. In this formulation, the covariance matrix of the model state is expressed in a limited number of modes. In the classical implementation some sort of normalization of the square-root matrix is required when variables...
The Kalman filter is a sequential estimation procedure that combines a stochastic dynamical model with observations in order to update the model state and the associated uncertainty. In the situation where no measurements are available the filter works as an uncertainty propagator. The most computationally demanding part of the Kalman filter is to propagate the covariance through the dynamical system,...
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