Open AccessAdapted wavelets by parameterization of wavelet bases for estimates of feature extraction of signals
Author(s) -
B R Manju,
Athul Rajendran
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1012/1/012033
Subject(s) - wavelet , cascade algorithm , parametrization (atmospheric modeling) , lifting scheme , second generation wavelet transform , wavelet transform , wavelet packet decomposition , representation (politics) , stationary wavelet transform , computer science , selection (genetic algorithm) , mathematics , discrete wavelet transform , pattern recognition (psychology) , algorithm , artificial intelligence , physics , quantum mechanics , politics , political science , law , radiative transfer
The work demonstrates the parameterization of filters coefficients of compactly supported wavelet to implement in the design of the best wavelet selection. The technique determines the best wavelet by means of a mathematical description and gives a representation in a single parameter for wavelets of finite length. The approach takes an input wavelet that is approximated to the best match. Through a choice of the parameter to adapt to the wavelet coefficients the perfect adaptation of the wavelet is achieved. For wavelet selection, the adaptive approximation carried out through parametrization addresses the challenge of visualization by setting up a Matlab programme that relies on the best selection with high potential to feature extraction of arbitrary signals.