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Table 1 Computational results for compressive sensing

From: Novel forward–backward algorithms for optimization and applications to compressive sensing and image inpainting

m-sparse signal Methods N = 1024, M = 512 N = 2048, M = 1024
CPU Iter CPU Iter
m = 50 Algorithm 1.1 17.2860 8219 60.6703 11,237
Algorithm 1.2 15.6780 2941 54.0610 4429
Algorithm 3.1 10.1545 1266 29.8420 1522
m = 60 Algorithm 1.1 30.3607 11,478 82.9704 13746
Algorithm 1.2 20.5542 3700 56.8577 4718
Algorithm 3.1 12.4216 1622 30.7309 1742
m = 70 Algorithm 1.1 39.9470 13,507 97.9897 15191
Algorithm 1.2 21.8114 4079 60.7027 5035
Algorithm 3.1 14.4815 1873 33.8620 1880
m = 90 Algorithm 1.1 112.9716 24,608 124.0622 17,415
Algorithm 1.2 30.4207 5683 72.1555 5793
Algorithm 3.1 24.9734 3121 38.2926 2137