Copy reference, caption or embed code

- Orthogonal Procrustes Analysis for Dictionary Learning in Sparse Linear Representation

Average reconstruction error ESNR in sparse representation using dictionary learnt by K-SVD (non-solid lines) and R-SVD (solid lines), for L = 10000 synthetic vectors varying the additive noise power (in the legend)
Averages are calculated over 100 trials and plotted versus update iteration count. Left: D ∈ R 50 × 100 with sparsity k = 5, Right: D ∈ R 100 × 200 with sparsity k = 10.
Average reconstruction error ESNR in sparse representation using dictionary learnt by K-SVD (non-solid lines) and R-SVD (solid lines), for L = 10000 synthetic vectors varying the additive noise power (in the legend) Averages are calculated over 100 trials and plotted versus update iteration count. Left: D ∈ R 50 × 100 with sparsity k = 5, Right: D ∈ R 100 × 200 with sparsity k = 10.
Go to figure page
Reference
Caption
Embed code