A multi-resolution filtered-x LMS algorithm based on discrete wavelet transform for active noise control. (January 2016) - Qiu, Z.; Lee, C.-M.; Xu, Z.H.; Sui, L.N.
Abstract: We have developed a new active control algorithm based on discrete wavelet transform (DWT) for both stationary and non-stationary noise control. First, the Mallat pyramidal algorithm is introduced to implement the DWT, which can decompose the reference signal into several sub-bands with multi-resolution and provides a perfect reconstruction (PR) procedure. To reduce the extra computational complexity introduced by DWT, an efficient strategy is proposed that updates the adaptive filter coefficients in the frequency domainDeepthi B.B using a fast Fourier transform (FFT). Based on the reference noise source, a 'Haar' wavelet is employed and by decomposing the noise signal into two sub-band (3-band), the proposed DWT-FFT-based FXLMS (DWT-FFT-FXLMS) algorithm has greatly reduced complexity and a better convergence performance compared to a time domain filtered-x least mean square (TD-FXLMS) algorithm. As a result of the outstanding time-frequency characteristics of wavelet analysis, the proposed DWT-FFT-FXLMS algorithm can effectively cancel both stationary and non-stationary noise, whereas the frequency domain FXLMS (FD-FXLMS) algorithm cannot approach this point. Highlights: A new active control algorithm based on discrete wavelet transform (DWT) is proposed, which update the adaptive filter coefficients in frequency domain. The proposed active control algorithm, so-called DWT-FFT-FXLMS algorithm is verified and compared with TD-FXLMS and FD-FXLMS algorithms. Simulation results suggest that the DWT-FFT-FXLMS algorithm is effective for both stationary and non-stationary noise cancellation.