Sentence examples for minimum variance filtering from inspiring English sources

In this paper an inverse QR decomposition based recursive least-squares algorithm for linearly constrained minimum variance filtering is proposed.

The resulting optimal filters are globally optimal within the unbiased minimum-variance filtering over all linear unbiased estimators.

This paper proposes a derivative-free version of nonlinear unbiased minimum variance filter for Mars entry navigation.

In order to design high order prediction minimum variance filters, a design procedure independent of the Diophantine Equation solution is used.

An exact, closed-form minimum variance filter is designed for a class of discrete time uncertain systems which allows for both multiplicative and additive noise sources.

With these performance indices, the optimal gains of the PVM α- β- γ filters are determined using a minimum-variance filter criterion.

Simulation results show that not only the filtering performance of the PTSKF is compatible to that of the previous proposed parameterized minimum-variance filter (PMVF) but also the computational complexity of the former is less intensive than that of the latter.

RAB representatives include Bayesian beamformers [5, 6] and spatial filters with eigenvector constraints [7, 8], which are implemented using linearly constrained minimum variance (LCMV) filters.

The blind Capon multiuser receivers implemented by linearly constrained minimum variance (LCMV) filters are designed to achieve this goal.

The semi-blind Capon multiuser receiver is designed to achieve the goal by the usage of linearly constrained minimum variance (LCMV) filters.

This paper is concerned with the design of transformation-based reduced-rank generalized sidelobe canceller (RRGSC) for the linearly constrained minimum variance (LCMV) filter.