Title :
On the approximate decorrelation property of the discrete wavelet transform for fractionally differenced processes
Author_Institution :
Univ. of Windsor, Ont., Canada
Abstract :
In this correspondence, we develop an asymptotic theory for the correlations of wavelet coefficients of the discrete wavelet transform (DWT) for fractionally differenced processes. It provides a theoretical justification for the approximate decorrelation property of the DWT for fractionally differenced processes. In addition, it provides insights on how the length of the wavelet filter affects the within scale correlations and the between scale correlations differently; for within scale correlations, increasing the length of the wavelet filter increases the rate of decay as the two wavelet coefficients get further apart, while for between scale correlations, using a wavelet filter that is long enough can reduce the between scale correlations even for wavelet coefficients that are close together.
Keywords :
approximation theory; correlation theory; decorrelation; discrete wavelet transforms; filtering theory; DWT; approximate decorrelation property; asymptotic theory; between scale correlations; discrete wavelet transform; filter length; fractionally differenced processes; long memory processes; rate of decay; scale correlations; wavelet coefficients; wavelet filter; within scale correlations; Atmospheric waves; Councils; Decorrelation; Discrete wavelet transforms; Filters; Finance; Least squares approximation; Parameter estimation; Wavelet coefficients; Wavelet transforms;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2002.807309