Signal Processing Methods for Music Transcription is the first book dedicated to uniting
research related to signal processing algorithms and models for various aspects of music …

Many sparse signal representation (SSR) algorithms have been developed in the past
decade. The advantages of SSR such as compact representations and super resolution lead …

Numerous signals arising from physiological and physical processes, in addition to being
non-stationary, are moreover a mixture of sustained oscillations and non-oscillatory …

Sparse signal representations and approximations from overcomplete dictionaries have
become an invaluable tool recently. In this paper, we develop a new, heuristic, graph …

Matching Pursuit (MP) aims at finding sparse decompositions of signals over redundant
bases of elementary waveforms. Traditionally, MP has been considered too slow an …

Taking advantage of the structures inherent in many sparse decompositions constitutes a
promising research axis. In this paper, we address this problem from a Bayesian point of …

In this paper, the issue of audio source separation from a single channel is addressed, ie,
the estimation of several source signals from a single observation of their mixture. This …

Sparse representations have emerged as a powerful tool in signal and information
processing, culminated by the success of new acquisition and processing techniques such …

In this paper, we improve iterative greedy search algorithms in which atoms are selected
serially over iterations, ie, one-by-one over iterations. For serial atom selection, we devise …

Several studies have pointed out the need for accurate mid-level representations of music
signals for information retrieval and signal processing purposes. In this paper, we propose a …