doi: 10.7763/IJET.2011.V3.230
Performance Comparison of STFT, WT, LMS and RLS Adaptive Algorithms in Denoising of Speech Signal
,
,
M. R. Amin
3,*
- 1 the Computer Science
- 2 Engineering Department, Jahangirnagar University, Savar, Dhaka 1342, Bngladesh
- 3 the Department of Electronics and Communications Engineering, East West University, 43 Mohakhali, Dhaka1212, Bangladesh
Abstract
Different types of noise cancellation techniques are prevalent in recent literatures. The performance of a particular technique depends on mean, variance and maximum amplitude of error. At the same time the process time of signal and complexity of practical implementation of circuits is also a measuring tool for performance of a technique. The objective of this paper is to compare performance among the short time Fourier transform (STFT), wavelet transform (WT), least mean square (LMS) and recursive least square (RLS) methods in cancellation of noise from a speech signal. The analysis of the paper provides us the way of selection of the best denoising technique based on the statistical parameters of the above four mentioned techniques.
Keywords
- Signal denoising
- CPU time
- statistical parameters of adaptive filter
- wavelet transform
- short-time Fourier transform
- least mean square and recursive least square
How to Cite
Mahbubul Alam, Md. Imdadul Islam, and M. R. Amin, "Performance Comparison of STFT, WT, LMS and RLS Adaptive Algorithms in Denoising of Speech Signal," International Journal of Engineering and Technology, vol. 3, no. 3, pp. 235-238, 2011. https://doi.org/ 10.7763/IJET.2011.V3.230
Copyright & License
Copyright © 2011 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).