A narrowband active noise control algorithm considering the harmonic distortion of the loudspeaker

2020 ◽  
Vol 64 (1-4) ◽  
pp. 229-235
Author(s):  
Yinshan Cai ◽  
Longlei Dong ◽  
Yanxin Zhou
Keyword(s):  
Noise Reduction ◽  
Control Algorithm ◽  
Detrimental Effect ◽  
Noise Control ◽  
Active Noise Control ◽  
Harmonic Distortion ◽  
Least Mean Square ◽  
Active Noise ◽  
Least Mean Square Algorithm ◽  
Conventional Algorithm

Electrodynamic loudspeakers are the main actuators of the active noise control system, and their harmonic distortion has a detrimental effect on the noise reduction of the system. To improve the performance, this paper proposes a novel narrowband active noise control algorithm with compensating the nonlinearity of the loudspeaker. In the proposed algorithm, the parameters of the controller are obtained by iteration through the filtered-x least mean square algorithm. Meanwhile, they are adjusted in real-time by establishing the online inverse model of the loudspeaker using the Volterra expansion. The simulation experiments for the typical loudspeaker model show that the proposed algorithm can dramatically improve noise reduction compared to the conventional algorithm.

ADAPTIVE NEURAL NETWORK FOR FEEDBACK ACTIVE NOISE CONTROL SYSTEM

2009 ◽  
Vol 12 (12) ◽  
pp. 86-93
Author(s):  
Tuan Van Huynh ◽  
Phuong Huu Nguyen ◽  
Long Ngoc Nguyen
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Descent Method ◽  
Gradient Descent Method ◽  
Least Mean Square ◽  
Dynamic Learning ◽  
Active Noise ◽  
On Line ◽  
Least Mean Square Algorithm ◽  
Feedback Active Noise Control

This paper presents a neural-based filtered-X least-mean-square algorithm (NFXLMS) active noise control (ANC) system. The saturation of the power amplifier in ANC system is considered. A method for compensating the saturation is proposed. On line dynamic learning algorithms based on the error gradient descent method is carried out. The convergence of the algorithm is proven using a discrete Lyapunov function. Simulation results are provided for illustration.

All-pass filtered x least mean square algorithm for narrowband active noise control

2018 ◽  
Vol 142 ◽  
pp. 1-10 ◽  
Author(s):  
Kuheli Mondal (Das) ◽  
Saurav Das ◽  
Aminudin Bin Hj Abu ◽  
Nozomu Hamada ◽  
Hoong Thiam Toh ◽  
...  
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Mean Square ◽  
Least Mean Square ◽  
Active Noise ◽  
Least Mean Square Algorithm

Psychoacoustic active noise control system based on empirical mode decomposition

2019 ◽  
Vol 67 (5) ◽  
pp. 332-349
Author(s):  
Yonghong Nie ◽  
Yu Liu ◽  
Guofeng Li ◽  
Ganqing Zhang
Keyword(s):  
Control System ◽  
Noise Reduction ◽  
Empirical Mode Decomposition ◽  
Noise Control ◽  
Active Noise Control ◽  
Peak Frequency ◽  
Least Mean Square ◽  
Shaping Filter ◽  
Active Noise ◽  
Mode Decomposition

A psychoacoustic active noise control (ANC) system based on empirical mode decomposition (EMD) is proposed and implemented to improve the noise reduction performance of the control system. The noise source signal is decomposed by EMD, and the psychoacoustic parameter â–œloudnessâ–? of each intrinsic mode function (IMF) is initially calculated in such a system. Thereafter, the high-pass psychoacoustic weighting filter used to shape the error and reference signals is designed adaptively and automatically according to the loudness, peak frequency, and amplitude of each IMF. Three different ANC systems are simulated, and the sound pressure levels and loudness of their residual error signals are compared. The results demonstrate that the filter designed using this method can restrain the components of noise sources with small loudness better than the A-weighting shaping filter, so that the proposed control system can improve the noise reduction compared to those of the filtered-x least mean square and A-weighting shaping filters. Finally, the computational complexity of the three ANC systems is analyzed and compared.

scholarly journals Dual-Zone Active Noise Control Algorithm

2019 ◽  
Vol 10 (1) ◽  
pp. 4
Author(s):  
Ran Wang ◽  
Xiaolin Wang ◽  
Jingwei Liu ◽  
Jun Yang
Keyword(s):  
Noise Reduction ◽  
Least Squares ◽  
Control Algorithm ◽  
Noise Control ◽  
Active Noise Control ◽  
Sound Field ◽  
Secondary Source ◽  
Sound Power ◽  
Control Zone ◽  
Active Noise

When active noise control (ANC) is applied to acquire a ‘quiet zone’, it may produce an increase in the sound power outside the quiet zone and a change in the primary sound field, which are undesirable in anti-detection and personal audio. To obtain a large noise reduction in the control zone and a small increase of sound power outside the control zone, three wideband ANC algorithms are proposed based on the acoustic contrast control (ACC), least-squares (LS), and least-squares with acoustic contrast control (SFR-ACC) algorithms. With a loudspeaker array as the secondary source, dual-zone ANC with directivity, which realizes noise reduction in one zone without changing the sound power in the other zone, is achieved. Compared with the traditional LS algorithm, the three algorithms proposed in this paper can not only realize that the sound power outside the control zone is increased by less than 1 dB, but also reduce the noise in the control zone by more than 10 dB, which provides a new solution to multi-zone ANC research.

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