Polynomial Estimation of Signals from Uncertain Observations Using Covariance Information
نویسندگان
چکیده
The least-squares νth-order polynomial filtering and fixed-point smoothing problems of uncertainly observed signals are considered. The proposed estimators do not require the knowledge of the state-space model generating the signal, but only the moments (up to the 2νth one) of the signal and the observation noise, as well as the probability that the signal exists in the observations.
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