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.
Highlights
Acoustic noise control is essential for reducing the noise level in modern society since noise seriously affects human health [1,2]
This paper presents a comprehensive review of the frequency-domain filtered-x least mean-square (FxLMS) algorithms
For the FxLMS algorithm, the output of the control filter is calculated on a sample-by-sample basis and there is only one-sample delay for the generation of the cancelling signal
Summary
Acoustic noise control is essential for reducing the noise level in modern society since noise seriously affects human health [1,2]. The partitioned-block FDAF (PBFDAF) algorithm was introduced for ANC to reduce the delay in the signal path [36,37,38,39] This is achieved by partitioning the whole impulse response into several small sections, but this method does not completely eliminate the input-output delay. The calculation of the adaptive filter output can be implemented directly using the time-domain convolution and the delay in the signal path is removed [40,41,42,43]. Two computationally efficient FDAF algorithms for ANC were proposed in [46,47] using the delayless approach in [48,49], but the delay in the filter adaptation is not removed. Simulations are carried out to evaluate the convergence performance and stability of the frequency-domain FxLMS algorithms
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