Comparative Study of Adaptive Algorithms for Identification of Filter Bank Coefficients of Wavelets
Raghavendra Sharma, V. P. Pyara · 2012
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 few iterations. 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.