Sentence examples for minimum variance linear from inspiring English sources

The GLS estimator is the minimum variance linear unbiased estimator.

Indeed, the computational complexity of the proposed method is roughly the same as the classic minimum variance linear prediction analysis approach.

Under these assumptions, OLS provides estimates of the linear parameters that are unbiased and have minimum variance among linear estimators.

At the beginning, most of Kalman filters are linear filters, which are the minimum variance state estimation of linear dynamic systems [5].

A new linear filter is designed in the linear minimum variance sense using the innovation analysis approach.

Based on the new augmented model, the local optimal linear filter is designed in the linear minimum variance sense.

At last, the distributed fusion filter is obtained based on the well-known fusion algorithm weighted by matrices in the linear minimum variance sense.

Based on the realization construction of state prediction and measurement update, Kalman filter can obtain the optimal estimation of state under the linear minimum variance criterion.

Local optimal linear estimators are designed by using the orthogonal projection principle, and the fusion estimators are designed by using a fusion rule weighted by matrices in the linear minimum variance sense.

Then local estimates are transmitted to the fusion center over a perfect connection, where a distributed fusion filter is obtained by using the well-known matrix-weighted fusion estimation algorithm in the linear minimum variance sense.

Using the minimax robust estimation principle and the unbiased linear minimum variance (ULMV) optimal estimation rule, the five robust weighted fusion time-varying Kalman filters are presented based on the worst-case conservative systems with the conservative upper bounds of noise variances.