DocumentCode
316671
Title
Filters for reconstruction of higher order moments
Author
Krishnamurthy, Vikram ; Evans, Jamie
Author_Institution
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
Volume
1
fYear
1997
fDate
2-4 Jul 1997
Firstpage
153
Abstract
We derive finite dimensional filters for the running sums of higher order moments of linear Gaussian systems. We also give filters for doubly stochastic AR models where the random AR parameter varies as a nonlinear function of a linear Gaussian process
Keywords
Gaussian processes; Kalman filters; autoregressive processes; filtering theory; higher order statistics; linear systems; parameter estimation; recursive filters; signal reconstruction; Kalman filter; doubly stochastic AR models; finite dimensional filters; higher order moments reconstruction; linear Gaussian process; linear Gaussian systems; nonlinear function; random AR parameter; recursive algorithm; Density measurement; Equations; Gaussian processes; Hidden Markov models; Kalman filters; Linearity; Nonlinear filters; Random variables; State estimation; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Signal Processing Proceedings, 1997. DSP 97., 1997 13th International Conference on
Conference_Location
Santorini
Print_ISBN
0-7803-4137-6
Type
conf
DOI
10.1109/ICDSP.1997.628000
Filename
628000
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