LINEAR ESTIMATION OF STATIONARY RANDOM SEQUENCES BY MINIMUM-PHASE SYSTEMS.

Study of the linear estimation problem for stationary random sequences with known signal and noise spectral densities, using minimum-phase systems, in the case of uncorrelated signal and noise. The optimum filter transfer function is obtained from the necessary condition for minimum mean-square error for a broad class of signals and an arbitrary noise. The explicit form of the transfer function, and the expression for the minimum error, which depends only on the signal and noise spectral densities, are obtained in the case of a Gauss-Markov signal.