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The quantification of large SNR for MLE of ARARMAX models

Research output: Contribution to conference › Paper › peer-review

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The quantification of large SNR for MLE of ARARMAX models. / Zou, Y.; Heath, W.P.
2010. 5108-5113 Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China.

Research output: Contribution to conference › Paper › peer-review

HarvardHarvard

Zou, Y & Heath, WP 2010, 'The quantification of large SNR for MLE of ARARMAX models', Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China, 15/12/09 - 18/12/09 pp. 5108-5113. https://doi.org/10.1109/CDC.2009.5399593

APA

Zou, Y., & Heath, W. P. (2010). The quantification of large SNR for MLE of ARARMAX models. 5108-5113. Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China. https://doi.org/10.1109/CDC.2009.5399593

CBE

Zou Y, Heath WP. 2010. The quantification of large SNR for MLE of ARARMAX models. Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China. https://doi.org/10.1109/CDC.2009.5399593

MLA

Zou, Y. and W.P. Heath The quantification of large SNR for MLE of ARARMAX models. Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, 15 Dec 2009, Shanghai, China, Paper, 2010. 6 p. https://doi.org/10.1109/CDC.2009.5399593

VancouverVancouver

Zou Y, Heath WP. The quantification of large SNR for MLE of ARARMAX models. 2010. Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China. doi: 10.1109/CDC.2009.5399593

Author

Zou, Y. ; Heath, W.P. / The quantification of large SNR for MLE of ARARMAX models. Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China.6 p.

RIS

TY - CONF

T1 - The quantification of large SNR for MLE of ARARMAX models

AU - Zou, Y.

AU - Heath, W.P.

PY - 2010/1/29

Y1 - 2010/1/29

N2 - Maximum likelihood estimation(MLE) is widely applied in system identification because it is consistent and has excellent convergence properties. However gradient based optimization of likelihood function might end up in local convergence. It is known that for ARMAX and ARARX models, providing a large enough Signal-to-Noise-Ratio(SNR) will avoid the potential local convergence. We show the same condition can be extended to ARARMAX models in this paper. To ease the application of this condition, the exact value of such SNR needs to be quantified. Here we realize the quantification by constrained optimization.

AB - Maximum likelihood estimation(MLE) is widely applied in system identification because it is consistent and has excellent convergence properties. However gradient based optimization of likelihood function might end up in local convergence. It is known that for ARMAX and ARARX models, providing a large enough Signal-to-Noise-Ratio(SNR) will avoid the potential local convergence. We show the same condition can be extended to ARARMAX models in this paper. To ease the application of this condition, the exact value of such SNR needs to be quantified. Here we realize the quantification by constrained optimization.

U2 - 10.1109/CDC.2009.5399593

DO - 10.1109/CDC.2009.5399593

M3 - Papur

SP - 5108

EP - 5113

T2 - Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference

Y2 - 15 December 2009 through 18 December 2009

ER -