A Modified Spectral PRP Conjugate Gradient Projection Method for Solving Large-Scale Monotone Equations and Its Application in Compressed Sensing

Table 5

Numerical performance in singular case.

Problem	Dim	Method	CPU-time	Ni	Nf
P7	500	MPPRP-M	0.907980	6684	20055
		MPPRP-W	0.823281	6684	20055
		MSDFPB	1.063594	6684	20055
		PRP	0.801892	6695	20088
		MPRP	0.856992	6684	20055
		TPRP	0.892188	6684	20055
		DFPB1	0.906388	6690	20073
		DFPB2	0.894474	6684	20055
		MHS	1.045179	6684	20055
P7	1000	MPPRP-M	1.742640	8424	25275
		MPPRP-W	1.787419	8424	25275
		MSDFPB	2.140070	8424	25275
		PRP	1.773320	8435	25308
		MPRP	1.878275	8424	25275
		TPRP	1.856212	8424	25275
		DFPB1	1.855210	8430	25293
		DFPB2	1.869769	8424	25275
		MHS	2.085814	8424	25275
P7	2000	MPPRP-M	3.712167	10616	31851
		MPPRP-W	4.182644	10616	31851
		MSDFPB	4.622078	10617	31855
		PRP	4.465109	10628	31888
		MPRP	4.716474	10617	31855
		TPRP	5.772379	10617	31855
		DFPB1	5.357838	10622	31870
		DFPB2	4.663553	10616	31852
		MHS	5.737888	10617	31855
P7	5000	MPPRP-M	20.734981	14412	43239
		MPPRP-W	21.112604	14413	43243
		MSDFPB	23.963617	14414	43252
		PRP	22.231907	14425	43283
		MPRP	23.381419	14414	43252
		TPRP	23.871918	14414	43252
		DFPB1	23.222197	14420	43269
		DFPB2	23.300951	14414	43252
		MHS	25.432421	14414	43252