Volume & Issue no: Volume 3, Issue 4, July - August 2014
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Title: |
Noise Cancellation Using Adaptive Filter for PCG Signal |
Author Name: |
Naveen Dewangan, and R. M. Potdar |
Abstract: |
Abstract: The objective of this paper is to serve as how Noise
can be combated using adaptive filter for PCG signal. The
problem of controlling the noise level has been one of the
research topic over the years. This paper focuses on Adaptive
filtering algorithms and some of the applications of adaptive
filter. The main concept is to use the LMS (Least-Mean-
Square) algorithm to develop an adaptive filter that can be
used in Adaptive noise Cancellation (ANC) application. In this
paper we will learn the various algorithms of LMS (Least
Mean Square), NLMS (Normalized Least Mean Square) and
RLS (Recursive Least Square) on MATLAB platform with the
intention to compare their performance in noise cancellation.
The adaptive filter in MATLAB with a noisy tone signal and
white noise signal and analyze the performance of algorithms
in terms of MSE (Mean Squared Error), percentage noise
removal, Signal to Noise Ratio, computational complexity and
stability. The Adaptive Filter maximizes the signal to noise
ratio & minimize the Mean Squared Error and compare their
performance with respect to stability. Adaptive Noise Canceller
is useful to improve the S/N ratio. The Adaptive Filter
minimizes the mean squared error between a primary input,
which is the noisy PCG, and a reference input, which is either
noise that is correlated in some way with the noise in the
primary input or a signal that is correlated only with PCG in
the primary input.
Keywords: LMS (Least Mean Square), NLMS (Normalized
Least Mean Square), RLS (Recursive Least Square), MSE (Mean
Squared Error). |
Cite this article: |
Naveen Dewangan, and R. M. Potdar , "
Noise Cancellation Using Adaptive Filter for PCG Signal" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 3, Issue 4, July - August 2014 , pp.
038-043 , ISSN 2278-6856.
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