A variable step-size transform-domain LMS algorithm based on minimum mean-square deviation for autoregressive process

Shengkui Zhao, Douglas L Jones, Zhihong Man, Suiyang Khoo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we investigate the optimal variable step-size approach for the transform-domain least-mean-square (TDLMS) algorithm to achieve fast convergence speed and low steady-state misadjustment. By minimizing the mean-square deviation (MSD) between the filter weight vector and the true vector, we derive and approximate the optimal variable step-size for the TDLMS algorithm given autoregressive (AR) process as input signals. The resulted variable step-size has simple formulation and easily-setting parameters. Computer simulation is demonstrated in the framework of adaptive system modeling with a fourth-order AR input process. The overall performance are observed superior to the existing popular variable step-size approaches of the TDLMS algorithm.

Original languageEnglish (US)
Title of host publicationProceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013
Pages968-971
Number of pages4
DOIs
StatePublished - Aug 19 2013
Event2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013 - Melbourne, VIC, Australia
Duration: Jun 19 2013Jun 21 2013

Publication series

NameProceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013

Other

Other2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013
CountryAustralia
CityMelbourne, VIC
Period6/19/136/21/13

Fingerprint

Mathematical transformations
Adaptive systems
Computer simulation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Zhao, S., Jones, D. L., Man, Z., & Khoo, S. (2013). A variable step-size transform-domain LMS algorithm based on minimum mean-square deviation for autoregressive process. In Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013 (pp. 968-971). [6566507] (Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013). https://doi.org/10.1109/ICIEA.2013.6566507

A variable step-size transform-domain LMS algorithm based on minimum mean-square deviation for autoregressive process. / Zhao, Shengkui; Jones, Douglas L; Man, Zhihong; Khoo, Suiyang.

Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013. 2013. p. 968-971 6566507 (Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhao, S, Jones, DL, Man, Z & Khoo, S 2013, A variable step-size transform-domain LMS algorithm based on minimum mean-square deviation for autoregressive process. in Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013., 6566507, Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013, pp. 968-971, 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013, Melbourne, VIC, Australia, 6/19/13. https://doi.org/10.1109/ICIEA.2013.6566507
Zhao S, Jones DL, Man Z, Khoo S. A variable step-size transform-domain LMS algorithm based on minimum mean-square deviation for autoregressive process. In Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013. 2013. p. 968-971. 6566507. (Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013). https://doi.org/10.1109/ICIEA.2013.6566507
Zhao, Shengkui ; Jones, Douglas L ; Man, Zhihong ; Khoo, Suiyang. / A variable step-size transform-domain LMS algorithm based on minimum mean-square deviation for autoregressive process. Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013. 2013. pp. 968-971 (Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013).
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