Title :
Kalman like filtering and smoothing for reciprocal sequences
Author :
Baccarelli, E. ; Cusani, R. ; Blasio, G. Di
Author_Institution :
INFOCOM Dept., Rome Univ., Italy
fDate :
27 Jun-1 Jul 1994
Abstract :
The MMSE filtering problem of reciprocal Gaussian sequences in additive white Gaussian noise is solved in a recursive and causal form. The solution, based on the innovations method, is expressed in terms of a set of recursive equations formally similar to those of the well-known Kalman filter; it gives as by-product the solution of the MMSE smoothing problems (fixed-point, fixed-interval, fixed-lag). The performance of the proposed estimators is also given by recursive expressions
Keywords :
Gaussian noise; Kalman filters; Markov processes; estimation theory; physics fundamentals; recursive filters; sequences; smoothing methods; white noise; Gaussian sequences; Kalman like filtering; MMSE filtering problem; additive white Gaussian noise; causal form; estimators; innovations method; performance; reciprocal sequences; recursive expressions; smoothing; AWGN; Equations; Filtering; Gaussian processes; Kalman filters; Markov processes; Recursive estimation; Smoothing methods; Statistics; Technological innovation;
Conference_Titel :
Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
Conference_Location :
Trondheim
Print_ISBN :
0-7803-2015-8
DOI :
10.1109/ISIT.1994.394848