TY - JOUR
T1 - Decorrelation Property of Discrete Wavelet Transform Under Fixed-Domain Asymptotics
JF - IEEE Transactions on Information Theory
Y1 - 2013
A1 - Chang,Xiaohui
A1 - Stein,Michael L.
KW - Business Analytics
AB - Theoretical aspects of the decorrelation propertyof the discrete wavelet transform when applied to stochastic processes have been studied exclusively from the increasing-domain perspective, in which the distance between neighboring observations stays roughly constant as the number of observations increases. To understand the underlying data-generating process and to obtain good interpolations, fixed-domain asymptotics, in which the number of observations increases in a fixed region, is often more appropriate than increasing-domain asymptotics. In the fixed-domain setting, we prove that, for a general class of inhomogeneous covariance functions, with suitable choice of wavelet filters, the wavelet transform of a nonstationary process has mostly asymptotically uncorrelated components.
VL - 59
U2 - a
U4 - 99245598720
ID - 99245598720
ER -