Filtering, smoothing and prediction for wide-band noise driven linear systems (Q1358705)

The aim of this article is to study the linear smoothing and prediction problems for the wide-band noise driven signal and the white noise driven observations. Using the integral representation of the wide-band noise, the authors prove the existence of a unique optimal smoother, and of a unique optimal predictor. It is worth to notice that while the optimal smoother is synthesized in the same (classical) form as that for the white noise driven systems, the results obtained for the optimal predictor are different in comparison with those for the white noise driven systems.