N-dimensional signals with M Gaussian chirps at a computational cost O (MN) instead of the
expected O (MN/sup 2/logN). At each iteration of the pursuit, the best Gabor atom is first
selected, and then, its scale and chirp rate are locally optimized so as to get a" good" chirp
atom, ie, one for which the correlation with the residual is locally maximized. A ridge theorem
of the Gaussian chirp dictionary is proved, from which an estimate of the locally optimal …