On the limitation of convex optimization for sparse signal segmentation

We show that convex optimization methods have fundamental properties that complicate performing signal segmentation based on sparsity assumptions. We review the recently introduced overcomplete sparse segmentation model, we perform experiments revealing the limits, and we explain this behaviour. We also propose modifications and alternatives.