MLMS-SUM Method LMS 결합 알고리듬을 적용한 웨이브렛 패킷 적응잡음제거기

Wavelet Packet Adaptive Noise Canceller with NLMS-SUM Method Combined Algorithm

Adaptive nois canceller can extract the noiseremoved spech in noisy speech signal by adapting the filter-coefficients to the background noise environment. A kind of LMS algorithm is one of the most popular adaptive algorithm for noise cancellation due to low complexity, good numerical property and the merit of easy implementation. However there is the matter of increasing misadjustment at voiced speech signal. Therefore the demanded speech signal may be extracted. In this paper, we propose a fast and noise robust wavelet packet adaptive noise canceller with NLMS-SUM method LMS combined algorithm. That is, we decompose the frequency of noisy speech signal at the base of the proposed analysis tree structure. NLMS algorithm in low frequency band can efficiently dliminate the effect of the low frequency noise and SUM method LMS algorithm at each high frequency band can remove the high frequency nosie. The proposed wavelet packet adaptive noise canceller is enhanced the more in SNR and according to Itakura-Satio(IS) distance, it is closer to the clean speech signal than any other previous adaptive noise canceller.