Theoretical analysis demonstrates explicit minimum mean square error expressions in noisy stationary discrete-time processes, highlighting a general procedure for linear estimation.
Several explicit expressions are presented for the minimum mean square error in linear causal filtering, prediction and interpolation of weakly stationary discrete-time processes corrupted by additive noise. A general procedure for deriving error expressions of this kind is established.
No takes yet. Share an insight, caveat, or question.
J. Snyders (1972) studied this question.
Synapse has enriched 3 closely related papers on similar clinical questions. Consider them for comparative context: