Feasibility Pump Algorithm for Sparse Representation under Laplacian Noise

Table 2

Mean relative errors (11) for SFP (top in each cell), SFPreg (middle), and RLAD (bottom) for matrix conditioning of 100000.

	5	7	9	11
SNR = 10	0.257	0.327	0.492	0.505
	0.253	0.252	0.263	0.256
	0.364	0.494	0.543	0.493
SNR = 20	0.086	0.086	0.185	0.445
	0.085	0.082	0.081	0.079
	0.143	0.224	0.438	0.406
SNR = 30	0.027	0.028	0.153	0.422
	0.027	0.027	0.026	0.025
	0.101	0.143	0.280	0.395
SNR =			0.023