Comparative Analysis for Least Mean Square and Normalized LMS for Speech Enhancement Application
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 7
Abstract
Adaptive Signal Processing (ASP) is an active research area. Adaptive Filter based speech enhancement technique is now a day’s getting very popular due to wide range of applications like mobile communication, hearing aids and speech recognition systems. Although this problem has attracted significant research efforts for several decades, many aspects remain open and require further research. The steady state levels of error, SNR and convergence performance of the widely-used adaptive algorithms haven’t been fully explored. This paper aims to investigate performance analysis and enhancements for the normalized least mean square adaptive algorithms and its application in speech enhancement. Objective of Implementing and analyzing the algorithms is to modify the algorithm to improve convergence behaviour, reduce computational requirements and decrease steady state mean square error. Experimental results revel that refined algorithms perform better than the existing algorithms.
Authors and Affiliations
D. Manoj Kumar, P. Surendra Kumar
Keywords
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