Abstract
A blind least-mean-squares (BLMS) algorithm is proposed for the parameter identification of single-input multiple-output (SIMO) systems. Without requiring knowledge of a reference signal, it is proved that the presented parameter estimates almost sure converge to their real value under the assumption that the observed noises are mutually independent distributed additive white sequence with known variance. The noise variance of observed signal is estimated from the eigenvalues of a matrix related to observed signal sequence firstly. We back our theoretical findings with experiments showcasing the potential merits of the BLMS in practice.
| Original language | English |
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| Title of host publication | ASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings |
| Pages | 1449-1453 |
| Number of pages | 5 |
| Publication status | Published - 2011 |
| Event | 8th Asian Control Conference, ASCC 2011 - Kaohsiung, Taiwan, Province of China Duration: 15 May 2011 → 18 May 2011 |
Publication series
| Name | ASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings |
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Conference
| Conference | 8th Asian Control Conference, ASCC 2011 |
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| Country/Territory | Taiwan, Province of China |
| City | Kaohsiung |
| Period | 15/05/11 → 18/05/11 |
Keywords
- Recursive identification
- almost sure convergence
- least-mean-squares
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Chen, J., Ma, T., Chen, W., & Zhang, B. (2011). Recursive blind LMS parameter identification for single-input multiple-output system. In ASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings (pp. 1449-1453). Article 5899286 (ASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings).