Sparse Time-Frequency Representation Via Atomic Norm Minimization
Tsubasa Kusano, Kohei Yatabe, Yasuhiro Oikawa
Abstract
Nonstationary signals are commonly analyzed and processed in the time-frequency (T-F) domain that is obtained by the discrete Gabor transform (DGT). The T-F representation obtained by DGT is spread due to windowing, which may degrade the performance of T-F domain analysis and processing. To obtain a well-localized T-F representation, sparsity-aware methods using ℓ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> -norm have been studied. However, they need to discretize a continuous parameter onto a grid, which causes a model mismatch. In this paper, we propose a method of estimating a sparse T-F representation using atomic norm. The atomic norm enables sparse optimization without discretization of continuous parameters. Numerical experiments show that the T-F representation obtained by the proposed method is sparser than the conventional methods.
BibTeX
@inproceedings{icassp2021_sparsetimefreque,
title = {Sparse Time-Frequency Representation Via Atomic Norm Minimization},
author = {Tsubasa Kusano and Kohei Yatabe and Yasuhiro Oikawa},
booktitle = {ICASSP 2021},
year = {2021}
}