Detail the limitations of Single Measurement Vector (SMV) recovery.

Introduce MSBL as a solution that jointly recovers signals sharing a common sparsity profile.

Summarize key results, such as improved accuracy at low signal-to-noise ratios (SNR).

Briefly state the problem of sparse signal recovery in models.