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Appl. Sci. 2018, 8(11), 2313; https://doi.org/10.3390/app8112313

Frequency-Domain Filtered-x LMS Algorithms for Active Noise Control: A Review and New Insights

1
State Key Laboratory of Acoustics and Key Laboratory of Noise and Vibration Research, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
2
Department of Electronics, Valahia University of Targoviste, Targoviste 130082, Romania
3
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Received: 23 October 2018 / Revised: 14 November 2018 / Accepted: 16 November 2018 / Published: 20 November 2018
(This article belongs to the Special Issue Active and Passive Noise Control)
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Abstract

This paper presents a comprehensive overview of the frequency-domain filtered-x least mean-square (FxLMS) algorithms for active noise control (ANC). The direct use of frequency-domain adaptive filters for ANC results in two kinds of delays, i.e., delay in the signal path and delay in the weight adaptation. The effects of the two kinds of delays on the convergence behavior and stability of the adaptive algorithms are analyzed in this paper. The first delay can violate the so-called causality constraint, which is a major concern for broadband ANC, and the second delay can reduce the upper bound of the step size. The modified filter-x scheme has been employed to remove the delay in the weight adaptation, and several delayless filtering approaches have been presented to remove the delay in the signal path. However, state-of-the-art frequency-domain FxLMS algorithms only remove one kind of delay, and some of these algorithms have a very high peak complexity and hence are impractical for real-time systems. This paper thus proposes a new delayless frequency-domain ANC algorithm that completely removes the two kinds of delays and has a low complexity. The performance advantages and limitations of each algorithm are discussed based on an extensive evaluation, and the complexities are evaluated in terms of both the peak and average complexities. View Full-Text
Keywords: Active noise control; frequency domain adaptive filter; computational complexity; delayless; causality Active noise control; frequency domain adaptive filter; computational complexity; delayless; causality
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Yang, F.; Cao, Y.; Wu, M.; Albu, F.; Yang, J. Frequency-Domain Filtered-x LMS Algorithms for Active Noise Control: A Review and New Insights. Appl. Sci. 2018, 8, 2313.

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