On the Prediction of a Class of Wide-Sense Stationary Random Processes
Juan Miguel Medina, Bruno Cernuschi-Frías · IEEE Transactions on Signal Processing · 2010
We prove that under suitable conditions, a multi-band wide sense stationary stochastic process can be linearly predicted at time with arbitrarily small error using past samples taken at uniform rate. This result generalizes previous similar results for band-limited signals. Moreover we prove that the prediction problem from uniform past samples is equivalent to a disjoint translates condition on the spectrum together with the divergence of a logarithmic integral. We also show that, for the band-limited case, under similar conditions, non uniform samples can be taken.