State Estimation Under Uncertain Observations with Unknown Statistics

Jitendra K. Tugnait; Abraham H. Haddad

doi:10.1109/TAC.1979.1101996

State Estimation Under Uncertain Observations with Unknown Statistics

Jitendra K. Tugnait^*, Abraham H. Haddad

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

Abstract

The asymptotic behavior of a Bayes optimal adaptive estimation scheme for a linear discrete-time system with interrupted observations is investigated. The interrupted observation mechanism is expressed in terms of a stationary two-state Markov chain. The transition probability matrix is unknown and can take values only from a finite set.

Original language	English (US)
Pages (from-to)	201-210
Number of pages	10
Journal	IEEE Transactions on Automatic Control
Volume	24
Issue number	2
DOIs	https://doi.org/10.1109/TAC.1979.1101996
State	Published - Apr 1979

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TAC.1979.1101996

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title = "State Estimation Under Uncertain Observations with Unknown Statistics",

abstract = "The asymptotic behavior of a Bayes optimal adaptive estimation scheme for a linear discrete-time system with interrupted observations is investigated. The interrupted observation mechanism is expressed in terms of a stationary two-state Markov chain. The transition probability matrix is unknown and can take values only from a finite set.",

author = "Tugnait, {Jitendra K.} and Haddad, {Abraham H.}",

year = "1979",

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AU - Tugnait, Jitendra K.

AU - Haddad, Abraham H.

PY - 1979/4

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N2 - The asymptotic behavior of a Bayes optimal adaptive estimation scheme for a linear discrete-time system with interrupted observations is investigated. The interrupted observation mechanism is expressed in terms of a stationary two-state Markov chain. The transition probability matrix is unknown and can take values only from a finite set.

AB - The asymptotic behavior of a Bayes optimal adaptive estimation scheme for a linear discrete-time system with interrupted observations is investigated. The interrupted observation mechanism is expressed in terms of a stationary two-state Markov chain. The transition probability matrix is unknown and can take values only from a finite set.

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JO - IEEE Transactions on Automatic Control

JF - IEEE Transactions on Automatic Control

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ER -

State Estimation Under Uncertain Observations with Unknown Statistics

Abstract

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