This paper presents the first theoretical results showing that stable
identification of overcomplete $\mu$-coherent dictionaries $\Phi \in
\mathbb{R}^{d\times K}$ is locally possible from training signals with sparsity
levels $S$ up to the order $O(\mu^{-2})$ and signal to noise ratios up to
$O(\sqrt{d})$. In particular the dictionary is recoverable as the <