doi: 10.7763/IJMO.2012.V2.142
Statistical Approach for Noise Removal in Speech Signals Using LMS, NLMS, Block LMS and RLS Adaptive filters
- Department of ECE
Abstract
In this paper the application of different adaptive filters in removing the noise present in the speech signals is presented. To analyze the performance of different adaptive filter family members, the parameters like convergence, output PSNR and CPU consumption time are considered. Results show that NLMS filter shows the better performance in CPU time consumption and output PSNR. Block LMS has the highest Convergence factor among all the members of the adaptive filter family.
Keywords
- Adaptive filters
- LMS
- RLS
- NLMS
- NLMS
How to Cite
D. Hari Hara Santosh, Vusl Sravya Pendyala, V. N. Lakshman Kumar, and N. Shanmukh Rao, "Statistical Approach for Noise Removal in Speech Signals Using LMS, NLMS, Block LMS and RLS Adaptive filters," International Journal of Modeling and Optimization, vol. 2, no. 3, pp. 351-355, 2012. https://doi.org/ 10.7763/IJMO.2012.V2.142
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).