Abstract
We propose an algorithm, called Bases Sorting, to sort the bases of over-complete dictionaries used in sparse representation according to the magnitudes of coefficients when representing the training samples. Then the bases are considered to be ordered from low to high frequencies, thus generalizing the traditional concept of frequency for over-complete dictionaries. Applications are also shown.
Type
Publication
Neurocomputing