We focus on the use of windows in the frequency domain processing of data for the purpose of Wiener filtering. Classical frequency domain asymptotics replace linear convolution by circulant convolution, leading to approximation errors. The introduction of windows can lead to slightly more complex frequency domain techniques, replacing diagonal matrices by banded matrices, but with controlled approximation error. Other work observed this recently, proposing general banded matrices in the frequency domain for filtering. Here, we emphasize the design of a window to optimize the banded approximation, and more importantly, we show that the whole banded matrix is in fact still parametrized by a diagonal matrix, which facilitates estimation. We propose here both some non-parametric and parametric approaches for estimating the diagonal spectral parts and revisit in particular the effect of the window on frequency domain Recursive Least-Squares (RLS) adaptive filtering.
Wiener filtering in the windowed DFT domain
EUSIPCO 2014, 22nd European Signal Processing Conference, September 1-5, 2014, Lisbon, Portugal
Systèmes de Communication
© 2014 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PERMALINK : https://www.eurecom.fr/publication/4467