scholarly journals Influence of modeling error on noise reduction performance of active noise control systems using filtered-X LMS algorithm.

1996 ◽  
Vol 17 (4) ◽  
pp. 195-202 ◽  
Author(s):  
Nozomu Saito ◽  
Toshio Sone
Keyword(s):  
Noise Reduction ◽  
Control Systems ◽  
Noise Control ◽  
Active Noise Control ◽  
Lms Algorithm ◽  
Modeling Error ◽  
Active Noise

Coherence-based performance analysis on noise reduction in multichannel active noise control systems

2020 ◽  
Vol 148 (3) ◽  
pp. 1519-1528
Author(s):  
Jihui Aimee Zhang ◽  
Naoki Murata ◽  
Yu Maeno ◽  
Prasanga N. Samarasinghe ◽  
Thushara D. Abhayapala ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Noise Reduction ◽  
Control Systems ◽  
Noise Control ◽  
Active Noise Control ◽  
Active Noise

scholarly journals Convex combination-based active impulse noise control system

2019 ◽  
Vol 39 (1) ◽  
pp. 190-202 ◽  
Author(s):  
Ning Yu ◽  
Zhaoxia Li ◽  
Yinfeng Wu ◽  
Renjian Feng ◽  
Bin Chen
Keyword(s):  
Control System ◽  
Noise Reduction ◽  
Impulse Noise ◽  
Noise Control ◽  
Convex Combination ◽  
Active Noise Control ◽  
Lms Algorithm ◽  
Frequency Noise ◽  
Active Noise ◽  
Risk Sensitive

Active noise control shows a good performance on the suppression of the low-frequency noise and hence it is widely applied. However, the traditional active noise control systems are unsatisfactory in controlling impulse noise in practical situations. A method based on the convex combination of filtered-x least mean square and filtered-x minimum kernel risk-sensitive loss adaptive algorithms (CFxLM) is presented to efficiently suppress impulse noise. Due to the simplicity of the LMS algorithm, the related filter is selected as the fast filter. Because the minimum kernel risk-sensitive loss algorithm is robust to impulse noise and can offer good convergence performance, we first apply it to the active noise control system and select the corresponding filter as the slow one. The proposed CFxLM algorithm can achieve both fast convergence and good noise reduction and any prior knowledge of reference noise is unnecessary. Extensive simulations demonstrate the superior noise reduction capability of the developed CFxLM-based active noise control system in controlling impulse noise.

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