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White noise deconvolution or input white noise estimation problem has important application backgrounds in oil seismic exploration, communication and signal processing. Using the modern time series analysis method, based on the autoregressive moving average (ARMA) innovation model and the optimal fusion rules in linear minimum variance sense, the new information fusion white noise deconvolution estimators...
For the multisensor multi-channel autoregressive moving average (ARMA) signals with time-delayed measurements, using the modern time series analysis method, based on the ARMA innovation model, under the linear minimum variance optimal weighted fusion rules, three distributed optimal information fusion Wiener filters weighted by matrices, diagonal matrices and scalars are presented, which can handle...
For the linear discrete time-invariant stochastic control systems with time-delayed measurements, they can be transformed into the systems without time-delayed measurements by introducing new measurement processes. Three distributed optimal information fusion Kalman filters weighted by matrices, diagonal matrices and scalars are presented in the linear minimum variance sense. They overcome the drawback...
White noise deconvolution or input white noise estimation problem has important application backgrounds in oil seismic exploration, communication and signal processing. By the modern time series analysis method, based on the auto-regressive moving average (ARMA) innovation model, under the linear minimum variance optimal fusion rules, three optimal weighted fusion white noise deconvolution estimators...
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