Abstract
In this paper a new type of bias-eliminated least-squares (BELS) based algorithm is proposed for consistent identification of linear systems with noisy input and output measurements. It is shown that estimation of the noise variances can be implemented when the degree of the denominator polynomial of the system transfer function is increased by one. The modified BELS algorithm is attractive and meaningful in that noisy data are used in identification with no prefiltering and a direct estimate of system parameters is given without any parameter transformation.
| Original language | English |
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| Title of host publication | Proceedings of the IEEE Conference on Decision and Control |
| Editors | Anon |
| Publication status | Published - 1996 |
| Event | Proceedings of the 1996 35th IEEE Conference on Decision and Control. Part 3 (of 4) - Kobe, Jpn Duration: 11 Dec 1996 → 13 Dec 1996 |
Publication series
| Name | Proceedings of the IEEE Conference on Decision and Control |
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| Volume | 1 |
| ISSN (Print) | 0191-2216 |
Conference
| Conference | Proceedings of the 1996 35th IEEE Conference on Decision and Control. Part 3 (of 4) |
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| City | Kobe, Jpn |
| Period | 11/12/96 → 13/12/96 |