Title :
A New Delayless Subband Adaptive Filtering Algorithm for Active Noise Control Systems
Author :
Milani, Ali A. ; Panahi, Issa M S ; Loizou, Philipos C.
Author_Institution :
Dept. of Electr. Eng., Univ. of Texas at Dallas, Richardson, TX
fDate :
7/1/2009 12:00:00 AM
Abstract :
Subband adaptive filtering (SAF) techniques play a prominent role in designing active noise control (ANC) systems. They reduce the computational complexity of ANC algorithms, particularly, when the acoustic noise is a broadband signal and the system models have long impulse responses. In the commonly used uniform-discrete Fourier transform (DFT)-modulated (UDFTM) filter banks, increasing the number of subbands decreases the computational burden but can introduce excessive distortion, degrading performance of the ANC system. In this paper, we propose a new UDFTM-based adaptive subband filtering method that alleviates the degrading effects of the delay and side-lobe distortion introduced by the prototype filter on the system performance. The delay in filter bank is reduced by prototype filter design and the side-lobe distortion is compensated for by oversampling and appropriate stacking of subband weights. Experimental results show the improvement of performance and computational complexity of the proposed method in comparison to two commonly used subband and block adaptive filtering algorithms.
Keywords :
active noise control; adaptive filters; computational complexity; discrete Fourier transforms; UDFTM-based adaptive subband filtering method; acoustic noise; active noise control systems; broadband signal; computational complexity; discrete Fourier transform; filter banks; side-lobe distortion; subband adaptive filtering algorithm; Acoustic distortion; Acoustic noise; Active noise reduction; Adaptive filters; Computational complexity; Control systems; Degradation; Delay; Filter bank; Filtering algorithms; Active noise control (ANC); discrete Fourier transform (DFT); filter bank; subband adaptive filter;
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
DOI :
10.1109/TASL.2009.2015691