Table 4 Numerical results with partial DCT sensing matrices for noisy data. The number of measurements m is m=n/8, and the test signals are s-sparse with s=0.01n. Each value in a cell represents the mean over 50 trials
From: A fast and accurate algorithm for ℓ 1 minimization problems in compressive sampling
Method | ℓ 2-error | ℓ 1-error | ℓ ∞ -error | CPU time(s) | Iterations | |
|---|---|---|---|---|---|---|
n=213 | ||||||
Algorithm 3 | 1.02e −1 | 1.94e −2 | 8.48e −1 | 0.3296 | 122 | |
DADM | 1.02e −1 | 1.94e −2 | 8.48e −1 | 0.2790 | 94 | |
NESTA | 1.20e −1 | 3.07e −2 | 1.0099 | 0.4606 | 145 | |
n=215 | ||||||
Algorithm 3 | 1.02e −1 | 1.83e −2 | 9.37e −1 | 1.5691 | 121 | |
DADM | 1.02e −1 | 1.82e −2 | 9.37e −1 | 1.4009 | 95 | |
NESTA | 1.22e −1 | 2.74e −2 | 1.1065 | 2.0506 | 149 | |
n=213 | ||||||
Algorithm 3 | 2.97e −2 | 5.30e −3 | 15.1517 | 0.2853 | 102 | |
DADM | 2.97e −2 | 5.21e −3 | 15.1429 | 0.3028 | 99 | |
NESTA | 3.10e −2 | 2.08e −2 | 17.2106 | 0.5012 | 160 | |
n=215 | ||||||
Algorithm 3 | 2.92e −2 | 5.89e −3 | 16.8347 | 1.5609 | 120 | |
DADM | 2.92e −2 | 5.79e −3 | 16.8203 | 1.4675 | 99 | |
NESTA | 3.16e −2 | 1.93e −2 | 19.4426 | 2.2300 | 160 | |
n=213 | ||||||
Algorithm 3 | 1.94e −3 | 2.87e −4 | 75.5390 | 0.3231 | 115 | |
DADM | 1.92e −3 | 3.49e −4 | 75.4992 | 0.6975 | 230 | |
NESTA | 1.93e −3 | 1.50e −3 | 90.2023 | 0.4981 | 157 | |
n=215 | ||||||
Algorithm 3 | 1.89e −3 | 2.00e −4 | 86.3350 | 1.5025 | 114 | |
DADM | 1.88e −3 | 2.06e −4 | 86.2110 | 3.3468 | 233 | |
NESTA | 2.03e −3 | 1.41e −3 | 99.4225 | 2.2662 | 158 | |