Download Structured sparsity for audio signals
Regression problems with mixed-norm priors on time-frequency coefficients lead to structured, sparse representations of audio signals. In this contribution, a systematic formulation of thresholding operators that allow for weighting in the time-frequency domain is presented. The related iterative algorithms are then evaluated on synthetic and real-life audio signals in the context of denoising and multi-layer decomposition. Further, initial results on the influence of the shape of the weighting masks are presented.
Download Constructing an invertible constant-Q transform with nonstationary Gabor frames
An efficient and perfectly invertible signal transform featuring a constant-Q frequency resolution is presented. The proposed approach is based on the idea of the recently introduced nonstationary Gabor frames. Exploiting the properties of the operator corresponding to a family of analysis atoms, this approach overcomes the problems of the classical implementations of constant-Q transforms, in particular, computational intensity and lack of invertibility. Perfect reconstruction is guaranteed by using an easy to calculate dual system in the synthesis step and computation time is kept low by applying FFT-based processing. The proposed method is applied to real-life signals and evaluated in comparison to a related approach, recently introduced specifically for audio signals.