scholarly journals Fractional lower order moment based adaptive algorithms for active noise control of impulsive noise sources

2012 ◽  
Vol 132 (6) ◽  
pp. EL456-EL462 ◽  
Author(s):  
Muhammad Tahir Akhtar
Keyword(s):  
Lower Order ◽  
Noise Control ◽  
Impulsive Noise ◽  
Active Noise Control ◽  
Adaptive Algorithms ◽  
Order Moment ◽  
Noise Sources ◽  
Active Noise

scholarly journals An adaptive algorithm, based on modified tanh non-linearity and fractional processing, for impulsive active noise control systems

2017 ◽  
Vol 37 (3) ◽  
pp. 495-508 ◽  
Author(s):  
Muhammad T Akhtar
Keyword(s):  
Adaptive Algorithm ◽  
Noise Control ◽  
Active Noise Control ◽  
Main Idea ◽  
Nonlinear Process ◽  
Order Moment ◽  
Least Mean Square ◽  
Noise Sources ◽  
Active Noise ◽  
Gradient Computation

This paper presents an adaptive algorithm for active control of noise sources that are of impulsive nature. The impulsive type sources can be better modeled as a stable distribution than the Gaussian. However, for stable distributions, the variance (second order moment) is infinite. The standard adaptive filtering algorithms, which are based on minimizing variance and assuming Gaussian distribution, converge slowly or become even unstable for stable (impulsive) processes. In order to improve the performance of the standard filtered-x least mean square (FxLMS)-based impulsive active noise control (IANC) systems, we propose two enhancements in this paper. First, we propose employing modified tanh function-based nonlinear process in the reference and error paths of the standard FxLMS algorithm. The main idea is to automatically give an appropriate weight to the various samples in the process, i.e. appropriately threshold the very large values so that system remains stable, and give more weight to samples below threshold limit so that the convergence speed can be improved. A second proposal is to incorporate the fractional-gradient computation in the update vector of IANC adaptive filter. Computer simulations have been carried out using experimental data for the acoustic paths. The simulation results demonstrate that the proposed algorithm is very effective for IANC systems.

scholarly journals An Evaluation of Active Noise Control in a Cylindrical Shell

1989 ◽  
Vol 111 (3) ◽  
pp. 337-342 ◽  
Author(s):  
R. J. Silcox ◽  
H. C. Lester ◽  
S. B. Abler
Keyword(s):  
Cylindrical Shell ◽  
Analytical Model ◽  
Noise Control ◽  
Active Noise Control ◽  
Effective Control ◽  
Elastic Cylindrical Shell ◽  
Noise Sources ◽  
Active Noise ◽  
Fixed Array ◽  
Forced Responses

This paper examines the physical mechanisms governing the use of active noise control in an extended volume of a cylindrical shell. Measured data were compared with computed results from a previously derived analytical model based on infinite shell theory. For both the analytical model and experiment, the radiation of external monopoles is coupled to the internal acoustic field through the radial displacement of the thin, elastic, cylindrical shell. An active noise control system was implemented inside the cylinder using a fixed array of discrete monopole sources, all of which lie in the plane of the exterior noise sources. Good agreement between measurement and prediction was obtained for both internal pressure response and overall noise reduction. Attenuations in the source plane greater than 15 dB were recorded along with a uniformly quieted noise environment over an indicative length inside the experimental model. Results indicate that for forced responses with extended axial distributions, axial arrays of control sources may be required. Finally, the Nyquist criteria for the number of azimuthal control sources is shown to provide for effective control over the full cylinder cross section.

Less complex solutions for active noise control of impulsive noise

2019 ◽  
Vol 102 (3) ◽  
pp. 507-521
Author(s):  
Alina Mirza ◽  
Ayesha Zeb ◽  
Mir Yasir Umair ◽  
Danish Ilyas ◽  
Shahzad Amin Sheikh
Keyword(s):  
Noise Control ◽  
Impulsive Noise ◽  
Active Noise Control ◽  
Active Noise ◽  
Complex Solutions
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