Signal stochastic decomposition over continuous dictionaries

Conference of 2014 24th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2014 ; Conference Date: 21 September 2014 Through 24 September 2014; Conference Code:109223International audienceWe propose a Bayesian nonparametrics method, including algorithm for posterior computation, for the sparse regression problem. Our method applies in a general setting, when there are direct or indirect noisy observations of the signal. We try to make a wide focus on smoothness properties and sparsity of the approximate. As an example, we consider the ill-posed inverse problem of Quantum Homodyne Tomography