@article {1969986,
	title = {Decorrelation Property of Discrete Wavelet Transform Under Fixed-Domain Asymptotics},
	journal = {IEEE Transactions on Information Theory},
	volume = {59},
	year = {2013},
	month = {2013},
	pages = {8001-8013},
	abstract = {Theoretical aspects of the decorrelation property of 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.},
	keywords = {Business Analytics},
	author = {Chang,Xiaohui and Stein,Michael L.}
}
