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Based on the optimal fusion algorithm weighted by scalars in the linear minimum variance sense, a distributed optimal fusion reduced-order Kalman filter with scalar weights is presented for discrete-time stochastic singular systems with multiple sensors and correlated noises. It has higher accuracy than any local filter does. Compared with the distributed fusion filter weighted by matrices, it has...
Based on white noise estimators and the optimal fusion algorithm in the LMV (linear minimum variance) sense, distributed optimal fusion steady-state smoothers with scalar weights are given for all components of discrete multichannel ARMA (autoregressive moving average) signals with correlated noises. The precision of the fusion smoothers is higher than that of local smoothers, but is lower than that...
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