The identification of errors-in-variables models with dynamics .

Michael Green; Brian D.O. Anderson

doi:10.1109/cdc.1985.268812

The identification of errors-in-variables models with dynamics .

Michael Green^*
, Brian D.O. Anderson

^*Corresponding author for this work

School of Engineering

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

2 Citations (Scopus)

Abstract

The authors consider the task of identifying a causal, linear, dynamic, multivariable system excited by stationary, zero-mean noise of unknown spectrum, and given measurements of the system inputs and outputs contaminated by independent, additive noise also of unknown spectra. Although the solution is in general not unique, finite-dimensional parameterizations of the solution set are given, even though the various spectra may not be rational.

Original language	English
Pages (from-to)	214-218
Number of pages	5
Journal	Proceedings of the IEEE Conference on Decision and Control
DOIs	https://doi.org/10.1109/cdc.1985.268812
Publication status	Published - 1985

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10.1109/cdc.1985.268812

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title = "The identification of errors-in-variables models with dynamics .",

abstract = "The authors consider the task of identifying a causal, linear, dynamic, multivariable system excited by stationary, zero-mean noise of unknown spectrum, and given measurements of the system inputs and outputs contaminated by independent, additive noise also of unknown spectra. Although the solution is in general not unique, finite-dimensional parameterizations of the solution set are given, even though the various spectra may not be rational.",

author = "Michael Green and Anderson, \{Brian D.O.\}",

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AU - Green, Michael

AU - Anderson, Brian D.O.

PY - 1985

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N2 - The authors consider the task of identifying a causal, linear, dynamic, multivariable system excited by stationary, zero-mean noise of unknown spectrum, and given measurements of the system inputs and outputs contaminated by independent, additive noise also of unknown spectra. Although the solution is in general not unique, finite-dimensional parameterizations of the solution set are given, even though the various spectra may not be rational.

AB - The authors consider the task of identifying a causal, linear, dynamic, multivariable system excited by stationary, zero-mean noise of unknown spectrum, and given measurements of the system inputs and outputs contaminated by independent, additive noise also of unknown spectra. Although the solution is in general not unique, finite-dimensional parameterizations of the solution set are given, even though the various spectra may not be rational.

UR - https://www.scopus.com/pages/publications/0022291845

U2 - 10.1109/cdc.1985.268812

DO - 10.1109/cdc.1985.268812

M3 - Conference article

AN - SCOPUS:0022291845

SN - 0191-2216

SP - 214

EP - 218

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

ER -

The identification of errors-in-variables models with dynamics .

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