Improved parameter estimation of linear systems with noisy data

Wei Xing Zheng

doi:10.1109/ISCAS.2000.858799

Improved parameter estimation of linear systems with noisy data

Wei Xing Zheng

School of Computer, Data & Mathematical Sciences

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

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Abstract

This paper addresses the problem of parameter estimation of linear systems with noisy input-output measurements. A new and simple estimation scheme for the variances of the white input and output measurement noises is presented which is based on expanding the denominator polynomial of the system transfer function only and makes no use of the average least-squares (LS) errors. The attractive feature of the iterative LS based parametric algorithm thus developed is its improved convergence property. The effectiveness of the developed identification algorithm is demonstrated through numerical illustrations.

Original language	English
Pages (from-to)	IV-505-IV-508
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	4
DOIs	https://doi.org/10.1109/ISCAS.2000.858799
Publication status	Published - 2000
Event	Proceedings of the IEEE 2000 International Symposium on Circuits and Systems, ISCAS 2000 - Geneva, Switz, Switzerland Duration: 28 May 2000 → 31 May 2000

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10.1109/ISCAS.2000.858799

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title = "Improved parameter estimation of linear systems with noisy data",

abstract = "This paper addresses the problem of parameter estimation of linear systems with noisy input-output measurements. A new and simple estimation scheme for the variances of the white input and output measurement noises is presented which is based on expanding the denominator polynomial of the system transfer function only and makes no use of the average least-squares (LS) errors. The attractive feature of the iterative LS based parametric algorithm thus developed is its improved convergence property. The effectiveness of the developed identification algorithm is demonstrated through numerical illustrations.",

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note = "Proceedings of the IEEE 2000 International Symposium on Circuits and Systems, ISCAS 2000 ; Conference date: 28-05-2000 Through 31-05-2000",

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AB - This paper addresses the problem of parameter estimation of linear systems with noisy input-output measurements. A new and simple estimation scheme for the variances of the white input and output measurement noises is presented which is based on expanding the denominator polynomial of the system transfer function only and makes no use of the average least-squares (LS) errors. The attractive feature of the iterative LS based parametric algorithm thus developed is its improved convergence property. The effectiveness of the developed identification algorithm is demonstrated through numerical illustrations.

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U2 - 10.1109/ISCAS.2000.858799

DO - 10.1109/ISCAS.2000.858799

M3 - Conference article

AN - SCOPUS:0033699226

SN - 0271-4310

VL - 4

SP - IV-505-IV-508

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

T2 - Proceedings of the IEEE 2000 International Symposium on Circuits and Systems, ISCAS 2000

Y2 - 28 May 2000 through 31 May 2000

ER -

Improved parameter estimation of linear systems with noisy data

Abstract

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