scholarly journals An improved narrowband active noise control system without secondary path modelling based on the time domain

2019 ◽  
Vol 15 (2/3) ◽  
pp. 110
Author(s):  
Hoong Thiam Toh ◽  
Waleed Fekry Faris ◽  
Akij Ahmad ◽  
Saikat Das ◽  
Aminudin Bin Hj. Abu ◽  
...  
Keyword(s):  
Control System ◽  
Time Domain ◽  
Noise Control ◽  
Active Noise Control ◽  
Active Noise ◽  
Path Modelling ◽  
The Time Domain

scholarly journals An improved narrowband active noise control system without secondary path modelling based on the time domain

2019 ◽  
Vol 15 (2/3) ◽  
pp. 110
Author(s):  
Kuheli Mondal ◽  
Saurav Das ◽  
Nozomu Hamada ◽  
Aminudin Bin Hj. Abu ◽  
Saikat Das ◽  
...  
Keyword(s):  
Control System ◽  
Time Domain ◽  
Noise Control ◽  
Active Noise Control ◽  
Active Noise ◽  
Path Modelling ◽  
The Time Domain

scholarly journals A Computationally Efficient Algorithm for Feedforward Active Noise Control Systems

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1504 ◽  
Author(s):  
Stefano Gaiotto ◽  
Antonino Laudani ◽  
Gabriele Maria Lozito ◽  
Francesco Riganti Fulginei
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Noise Control ◽  
Active Noise Control ◽  
Parameter Tuning ◽  
Processing Load ◽  
Block Basis ◽  
Active Noise ◽  
Wide Range ◽  
The Time Domain

In this paper, a novel algorithm with high computational efficiency is proposed for the filter adaptation in a feedforward active noise control system. The proposed algorithm Zero Forcing Block Adaptive Filter (ZF-BAF) performs filter adaptation on a block-by-block basis in the frequency domain. Filtering is performed in the time domain on a sample-by-sample basis. Working in the frequency domain permits us to get sub-linear complexity, whereas filtering in the time domain minimizes the latency. Furthermore, computational burden is tunable to meet specific requirements about adaptation speed and processing load. No other parameter tuning according to the working condition is required. Computer simulations, performed in different realistic cases against other high-performing time and frequency-domain algorithms, show that achievable performances are comparable, or even better, with those of the algorithms perfectly tuned for each specific case. Robustness exhibited in the tests suggests that performances are expected to be even better in a wide range of real cases where it is impossible to know a priori how to tune the algorithms.

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