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1 September 1995 Wavelet analysis of random fields and multiresolution Wiener filtering
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We explore the relationship between random processes and wavelets in multiple dimensions and their application to statistical signal processing. To this end, we introduce a multiresolution Wiener filter (MWF) that is applied to the wavelet coefficients of a random process. The MWF is based upon the multiresolution Wiener-Hopf (MWH) equation, which is derived using orthogonal projection theorem on a Hilbert space. The MWH is applied to the solution of the signal estimation problem for both stationary and fractional Brownian motion (fBm) processes. A theoretical mean square error is calculated for the MWF and its values compared to experimental data.
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Kevin West Bowman and Christian Houdre "Wavelet analysis of random fields and multiresolution Wiener filtering", Proc. SPIE 2569, Wavelet Applications in Signal and Image Processing III, (1 September 1995);

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