An introduction to wavelets
Multirate systems and filter banks
Multirate systems and filter banks
Minimum-bandwidth discrete-time wavelets
Signal Processing
Wavelet-based estimation of 1/f-type signal parameters: confidenceintervals using the bootstrap
IEEE Transactions on Signal Processing
Editorial: 2nd Special Issue on Statistical Signal Extraction and Filtering
Computational Statistics & Data Analysis
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A semi-parametric bootstrap procedure is proposed for two-dimensional spatial processes on a finite lattice (images). Discrete wavelet transforms are used to produce coefficients that are approximately uncorrelated in space. For illustration, realizations of spatial processes from the Matern class of spectral density functions are analyzed. The goal is to obtain bootstrap realizations by applying the nai@?ve bootstrap to the approximately uncorrelated wavelet coefficients. The methodology is shown to be effective at reproducing moderate levels of spatial covariance on several simulated data sets as well as images taken from a functional magnetic resonance imaging (fMRI) experiment. An application to testing functional connectivity in fMRI is also presented.