### Abstract

In this paper, X-block least-mean-square (LMS) adaptive algorithms are presented for time-and frequency-domain active noise control. The algorithms are essentially extensions of the well-known block-mean-square (BLMS) algorithms to the filtered-X structure. The X-filter block algorithms are formulated for time- and frequency-domain implementation. In addition, time varying convergence factors are derived for all the X-block LMS algorithms presented. Time-varying convergence factors improve the adaptation speed of the algorithm at the expense of additional computational complexity. The complexity of the proposed algorithms is also discussed and the computational efficiency of frequency-domain implementations is evaluated with different filter lengths. The algorithms are applied to active noise control and results are presented with computer simulations and real-time experiments.

Original language | English (US) |
---|---|

Pages (from-to) | 281-293 |

Number of pages | 13 |

Journal | Noise Control Engineering Journal |

Volume | 44 |

Issue number | 6 |

State | Published - Nov 1996 |

### Fingerprint

### ASJC Scopus subject areas

- Engineering (miscellaneous)
- Acoustics and Ultrasonics

### Cite this

*Noise Control Engineering Journal*,

*44*(6), 281-293.

**Time- and frequency-domain X-block least-mean-square algorithms for active noise control.** / Shen, Qun; Spanias, Andreas.

Research output: Contribution to journal › Article

*Noise Control Engineering Journal*, vol. 44, no. 6, pp. 281-293.

}

TY - JOUR

T1 - Time- and frequency-domain X-block least-mean-square algorithms for active noise control

AU - Shen, Qun

AU - Spanias, Andreas

PY - 1996/11

Y1 - 1996/11

N2 - In this paper, X-block least-mean-square (LMS) adaptive algorithms are presented for time-and frequency-domain active noise control. The algorithms are essentially extensions of the well-known block-mean-square (BLMS) algorithms to the filtered-X structure. The X-filter block algorithms are formulated for time- and frequency-domain implementation. In addition, time varying convergence factors are derived for all the X-block LMS algorithms presented. Time-varying convergence factors improve the adaptation speed of the algorithm at the expense of additional computational complexity. The complexity of the proposed algorithms is also discussed and the computational efficiency of frequency-domain implementations is evaluated with different filter lengths. The algorithms are applied to active noise control and results are presented with computer simulations and real-time experiments.

AB - In this paper, X-block least-mean-square (LMS) adaptive algorithms are presented for time-and frequency-domain active noise control. The algorithms are essentially extensions of the well-known block-mean-square (BLMS) algorithms to the filtered-X structure. The X-filter block algorithms are formulated for time- and frequency-domain implementation. In addition, time varying convergence factors are derived for all the X-block LMS algorithms presented. Time-varying convergence factors improve the adaptation speed of the algorithm at the expense of additional computational complexity. The complexity of the proposed algorithms is also discussed and the computational efficiency of frequency-domain implementations is evaluated with different filter lengths. The algorithms are applied to active noise control and results are presented with computer simulations and real-time experiments.

UR - http://www.scopus.com/inward/record.url?scp=0030283097&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0030283097&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0030283097

VL - 44

SP - 281

EP - 293

JO - Noise Control Engineering Journal

JF - Noise Control Engineering Journal

SN - 0736-2501

IS - 6

ER -