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Comparative Study of Adaptive Algorithms for Identification of Filter Bank Coefficients of Wavelets

Published on May 2012 by Raghavendra Sharma, V Prem Pyara
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National Conference on Advancement of Technologies – Information Systems and Computer Networks
Foundation of Computer Science USA
ISCON - Number 2
May 2012
Authors: Raghavendra Sharma, V Prem Pyara
284d6bf1-0033-4ef4-9589-3698ad824449

Raghavendra Sharma, V Prem Pyara . Comparative Study of Adaptive Algorithms for Identification of Filter Bank Coefficients of Wavelets. National Conference on Advancement of Technologies – Information Systems and Computer Networks. ISCON, 2 (May 2012), 21-25.

@article{
author = { Raghavendra Sharma, V Prem Pyara },
title = { Comparative Study of Adaptive Algorithms for Identification of Filter Bank Coefficients of Wavelets },
journal = { National Conference on Advancement of Technologies – Information Systems and Computer Networks },
issue_date = { May 2012 },
volume = { ISCON },
number = { 2 },
month = { May },
year = { 2012 },
issn = 0975-8887,
pages = { 21-25 },
numpages = 5,
url = { /proceedings/iscon/number2/6466-1013/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advancement of Technologies – Information Systems and Computer Networks
%A Raghavendra Sharma
%A V Prem Pyara
%T Comparative Study of Adaptive Algorithms for Identification of Filter Bank Coefficients of Wavelets
%J National Conference on Advancement of Technologies – Information Systems and Computer Networks
%@ 0975-8887
%V ISCON
%N 2
%P 21-25
%D 2012
%I International Journal of Computer Applications
Abstract

In this paper, a technique to identify the filter bank coefficients of Wavelets db4 and coif5 using adaptive filter NLMS algorithm is presented. Filter bank coefficients of the wavelet are treated as the weight vector of adaptive filter, changes with each iteration and approach to the desired value after little iteration. When we compare the two adaptive algorithms viz. Least Mean Square (LMS) and Normalized Least Mean Square (NLMS), NLMS performs better due to its insensitivity to step size, faster convergence and better accuracy. New Scaling and wavelet functions of the Wavelets db4 and coif5 are generated with the filter bank coefficients obtained by NLMS algorithm iteratively.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Approximation Coefficients Detail Coefficients Filter Bank Quadrature Mirror Filters