Abstract
The problem is considered of estimating a signal based on measurements with multiple packet dropouts when the probability of data arrival at a processing unit is known. Assuming that the equation which describes the signal is unknown, we derive recursive algorithms for the prediction, filtering and smoothing problems using the information provided by the covariance functions of the processes involved in the measurement equation.
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