SEQUENTIAL DECOMPOSITION OF THE PARTIALLY SINGULAR DISCRETE TIME FILTERING PROBLEM.

B. Priel; U. Shaked

doi:10.1109/cdc.1986.267538

SEQUENTIAL DECOMPOSITION OF THE PARTIALLY SINGULAR DISCRETE TIME FILTERING PROBLEM.

B. Priel^*, U. Shaked

^*Corresponding author for this work

School of Electrical Engineering

Tel Aviv University

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

A sequential decomposition method is developed for solving the stationary discrete-time algebraic matrix Riccati equation. This decomposition is applied to the partially singular stationary filtering problem where some of the system outputs are free of measurement noise. Explicit expressions are obtained for the minimum error covariance matrices in the case where the number of the noise free measurements is equal to the number of independent inputs.

Original language	English
Pages (from-to)	1048-1053
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
DOIs	https://doi.org/10.1109/cdc.1986.267538
State	Published - 1986

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title = "SEQUENTIAL DECOMPOSITION OF THE PARTIALLY SINGULAR DISCRETE TIME FILTERING PROBLEM.",

abstract = "A sequential decomposition method is developed for solving the stationary discrete-time algebraic matrix Riccati equation. This decomposition is applied to the partially singular stationary filtering problem where some of the system outputs are free of measurement noise. Explicit expressions are obtained for the minimum error covariance matrices in the case where the number of the noise free measurements is equal to the number of independent inputs.",

author = "B. Priel and U. Shaked",

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AB - A sequential decomposition method is developed for solving the stationary discrete-time algebraic matrix Riccati equation. This decomposition is applied to the partially singular stationary filtering problem where some of the system outputs are free of measurement noise. Explicit expressions are obtained for the minimum error covariance matrices in the case where the number of the noise free measurements is equal to the number of independent inputs.

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SEQUENTIAL DECOMPOSITION OF THE PARTIALLY SINGULAR DISCRETE TIME FILTERING PROBLEM.

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