  We propose a fast greedy algorithm to compute sparse representations of
signals from continuous dictionaries that are factorizable, i.e., with atoms
that can be separated as a product of sub-atoms. Existing algorithms strongly
reduce the computational complexity of the sparse decomposition of signals in
discrete factorizable dictionaries. On another flavour, existing greedy
algorithms use interpolation strategies from a discretization of continuous
dictionaries to perform off-the-grid decomposition. Our algorithm aims to
combine the factorization and the interpolation concepts to enable low
complexity computation of continuous sparse representation of signals. The
efficiency of our algorithm is highlighted by simulations of its application to
a radar system.
