We introduce a nondiagonal seismic denoising method based on the continuous wavelet
transform with hybrid block thresholding (BT). Parameters for the BT step are adaptively …

Recent advances in audio declip** have substantially improved the state of the art. Yet,
practitioners need guidelines to choose a method, and while existing benchmarks have …

This paper introduces a new Markov Chain Monte Carlo method for Bayesian variable
selection in high dimensional settings. The algorithm is a Hastings-Metropolis sampler with …

Audio signals such as music are known to exhibit distinct and sparse time-frequency
patterns. In particular, the short-time Fourier/Gabor transform is widely used for sparsely …

Natural audio signals are known to be highly structured. Incorporating knowledge about this
inherent structure helps to improve audio restoration algorithms. In this article audio …

Some audio declip** methods produce waveforms that do not fully respect the actual
process of clip** and allow a deviation on the reliable samples. This article reports what …

This paper addresses signal denoising when largeamplitude coefficients form clusters
(groups). The L1-norm and other separable sparsity models do not capture the tendency of …

Matching Pursuit (MP) is a greedy algorithm that iteratively builds a sparse signal
representation. This work presents an analysis of MP in the context of audio denoising. By …

In this paper, we present novel strategies for stationary/transient signal separation in audio
signals in order to exploit the basic observation that stationary components are sparse in …