Title :
Simulation and Performance Analysis of LMS and NLMS Adaptive Filters in Non-stationary Noisy Environment
Author :
Borisagar, Komal R. ; Sedani, Bhavin S. ; Kulkarni, G.R.
Author_Institution :
Dept. of Electron. & Commun., J.J.T. Univ., Rajkot, India
Abstract :
One of the most important applications of adaptive filter is Interference or noise cancellation. The objective of adaptive interference cancellation is to obtain an estimate of the interfering signal and to subtract it from the corrupted signal and hence obtain a noise free signal. The tracking performances of the LMS and NLMS algorithms are compared when the input of the adaptive filter is no stationary For this purpose, the filter uses an adaptive algorithm to change the value of the filter coefficients, so that it acquires a better approximation of the signal after each iteration. The LMS (Least Mean Square), and its variant the NLMS (Normalized LMS) are two of the adaptive algorithms widely in use. This paper presents a comparative analysis of the LMS and the NLMS in case of interference cancellation from speech signals. For each algorithm, the effects of two parameters-filter length and step size have been analyzed. Finally, the performances of the two algorithms in different cases have been compared.
Keywords :
adaptive filters; interference suppression; least mean squares methods; speech processing; LMS algorithm; NLMS adaptive filter; adaptive interference cancellation; filter coefficient; least mean square algorithm; noise cancellation; nonstationary noisy environment; normalized LMS algorithm; speech signal; tracking performance; Adaptive filters; Filtering algorithms; Filtering theory; Least squares approximation; Signal processing algorithms; Speech; Transversal filters; Adaptive Filter; LMS; NLMS; Step size;
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2011 International Conference on
Conference_Location :
Gwalior
Print_ISBN :
978-1-4577-2033-8
DOI :
10.1109/CICN.2011.148
