%0 Journal Article
%T Comparative Analysis and Design of Statistical Estimation for Various Adaptive Algorithms in Speech Signal Processing
%A J. Jebastine
%A B. Sheela Rani
%J International Journal of Advanced Electrical and Electronics Engineering
%D 2012
%I 
%X Effective noise deportation in an acoustic environment is a very essential criteria in the field of telecommunication and signal processing since it is highly preferable to have a noiseless system. Noise problems in the environment have gained attention, as noise levels have been increasing due to the tremendous growth of technology that has led to noisy engines, heavy machinery, high speed wind buffeting and other noise sources. The problem of reducing the noise level has become the focus of a burgeoning field of research over the years. Adaptive filters came into existence to solve this hitch and it has become one of the well known and most popular approaches for the processing and analysis of speech signal. Adaptive filtering is an important basis for signal processing, in recent years has developed rapidly in various fields on a wide range of applications. This proposal focuses on the comparison of various algorithms of adaptive filters and also strives to remove the White Gaussian Noise from the original speech signal. The algorithms employed are LMS, NLMS, B- LMS, FxBLMS, RLS, and FxT-RLS. The statistical parameters using which the algorithms are analyzed and compared are Convergence speed, power spectral density, Signal to Noise ratio, stability and percentage noise removal. The performances of the various algorithms are compared by simulation using MATLAB. Based on the statistical parameters the unrivaled algorithm among all is resolved for effective noise cancellation in speech signal.
%K Noise Cancellation
%K Adaptive Algorithm
%K Statistical parameters
%U http://irdindia.in/Journal_IJAEEE/PDF/Vol1_Iss3/8.pdf