Recursive filtering and smoothing for reciprocal Gaussian processes-pinned boundary case

Author

Baccarelli, E. ; Cusani, R. ; Di Blasio, G.

Author_Institution

INFOCOM Dept., Rome Univ., Italy

Volume

41

Issue

1

fYear

1995

fDate

1/1/1995 12:00:00 AM

Firstpage

334

Lastpage

337

Abstract

The least square estimation problem for pinned-to-zero discrete-index reciprocal Gaussian processes in additive white noise is solved, thus completing and extending some previous results available in the literature. In particular, following the innovations approach a (finite) set of recursive equations is obtained for the filter and for the three standard classes of smoothers (fixed-point, fixed-interval, fixed-lag). Recursive expressions for the mean square performance of the proposed estimators are also given

Keywords

Gaussian noise; least mean squares methods; recursive estimation; recursive filters; smoothing methods; white noise; AWGN; additive white noise; fixed-interval smoother; fixed-lag smoother; fixed-point smoother; least square estimation problem; mean square performance; pinned boundary case; pinned-to-zero discrete-index reciprocal Gaussian processes; reciprocal Gaussian processes; recursive equations; recursive filtering; smoothing; Additive white noise; Associate members; Blind equalizers; Computer aided software engineering; Equations; Filtering; Gaussian processes; Least squares approximation; Smoothing methods; Technological innovation;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/18.370087

Filename

370087