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Least-squares linear one-stage prediction, filtering and fixed-point smoothing algorithms for signal estimation using measurements with stochastic delays contaminated by additive white noise are derived. The delay is considered to be random and modelled by a binary white noise with values zero or one; these values indicate that the measurements arrive in time or they are delayed by one sampling time...
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