Reexamination of the prefiltering problem in a state-variable formulation (Corresp.)

Optimal (least-mean-square linear) filtering of random signals prior to sampling may be represented as a Wiener-Kalman state-variable filter followed by a coder that synthesizes the signal to be sampled as a linear combination of the estimated states. Although the prefilter doubles the number of states of the overall presampling signal process, the postsampling reconstruction filter need only model the original signal generator and the coder. Overall optimization involves selecting the parameters of the coder to minimize a weighted time-averaged error criterion.