Title :
Convergence improvement of the LMS adaptive noise canceller using low distortion filter banks
Author :
Noor, Ali O Abid ; Abdul Samad, Salina ; Hussain, Aini
Author_Institution :
Dept. of Electr., Electron. & Syst. Eng., Univ. Kebangsaan Malaysia (UKM), Bangi, Malaysia
Abstract :
This paper presents a subband least mean square LMS noise canceller with improved convergence behaviour. This improvement is achieved by modifying and optimizing an existing multirate filter bank that is used to improve the performance of full-band LMS adaptive filters. The optimized oversampled subband noise canceller offers a simplified structure that without employing cross-filters or gap filter banks reduces the total input/output distortion in speech signals. Issues of increasing convergence speed and decreasing the residual noise at the system output are addressed. Performances under white and colored environments are evaluated experimentally in terms of mean square error MSE performance. Compared to an equivalent oversampled scheme, fast initial convergence and better noise reduction performance can be obtained with this approach.
Keywords :
channel bank filters; interference suppression; least mean squares methods; signal denoising; LMS adaptive noise canceller; MSE performance; equivalent oversampled scheme; full-band LMS adaptive filters; least mean square; low distortion filter banks; mean square error; residual noise; subband noise canceller; Adaptive filters; Convergence; Distortion; Filter bank; Least squares approximation; Mean square error methods; Noise cancellation; Performance evaluation; Speech enhancement; Working environment noise; LMS algorithm; Noise cancellation; adaptive filtering; filters banks; subband filtering;
Conference_Titel :
Signal and Image Processing Applications (ICSIPA), 2009 IEEE International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-5560-7
DOI :
10.1109/ICSIPA.2009.5478720