Abstract
In this work we characterize random processes which can be linearly determined using a frame sequence of random variables. In particular, these could be the discrete samples of a continuous time process. We study the stable representation of continuous time processes by means of discrete samples or measurements of the original process. Finally, we study how these representations can be applied to reduce the effects of reconstructing a random signal from samples corrupted by additive noise.
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