• Ch Anoosha
• K Yashoda
• D Nagamani

The Adaptive noise cancellation algorithm is the popular technology for noise cancellation. There are different adaptive algorithms such as Least Mean Squares (LMS) algorithm, Normalized Least Mean Squares (NLMS), etc. all has their own merits and demerits, and their improvement algorithms are different. In practical applications, such as speech signal which is corrupted by high background noise need to be processed to extract useful signal and suppress noise. By studying the adaptive noise cancellation(ANC) principles, for speech enhancement this paper uses the optimal regularization NLMS algorithm to improve its application in noise cancellation and compares the simulation results with traditional NLMS algorithm. The performance of these techniques is compared with parameters such as SNR, true and estimated weights, and true and estimated noise. From simulation results both NLMS and the regularization NLMS can suppress noise but the regularization NLMS algorithm has a better ability to suppress noise and faster convergence.

NLMS; the regularization NLMS; Adaptive filter

"COMPARISON ON PERFORMANCE OF NLMS AND OPTIMAL REGULARIZATION NLMS ALGORITHMS FOR SPEECH ENHANCEMENT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.190-193, July-2018, Available :http://www.jetir.org/papers/JETIR1807032.pdf

"COMPARISON ON PERFORMANCE OF NLMS AND OPTIMAL REGULARIZATION NLMS ALGORITHMS FOR SPEECH ENHANCEMENT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp190-193, July-2018, Available at : http://www.jetir.org/papers/JETIR1807032.pdf