Thresholded smoothed-ℓ0(SL0) dictionary learning for sparse representations

In this paper, we suggest to use a modified version of Smoothed-ℓ0 (SL0) algorithm in the sparse representation step of iterative dictionary learning algorithms. In addition, we use a steepest descent for updating the non unit column-norm dictionary instead of unit column-norm dictionary. Moreover, to do the dictionary learning task more blindly, we estimate the average number of active atoms in the sparse representation of the training signals, while previous algorithms assumed that it is known in advance. Our simulation results show the advantages of our method over K-SVD in terms of complexity and performance.