In 2019 27th European Signal Processing Conference (EUSIPCO), pages 1-5, Sep., 2019. Paper doi abstract bibtex
In this paper, we analyze by means of simulations the applicability of random Gabor multipliers as compressive measurements. In particular, we consider signals that are sparse with respect to Fourier or Gabor dictionaries, i.e., signals that are sparse in frequency or time-frequency domains. This work is an extension of our earlier contribution, where we introduced random Gabor multipliers to compress signals that are sparse in time domain. As reconstruction technique we employ the well known ℓ1-minimization procedure. Finally, we evaluate the compression performance of random Gabor multipliers by applying them to a specific audio signal with inherent time-frequency sparsity. Our results highlight the strong potential of random Gabor multipliers for present and future real-world audio applications.