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Theory and Modern Applications

Table 2 Relative error and computational time for Example 5.2

From: Convergence analysis of gradient-based iterative algorithms for a class of rectangular Sylvester matrix equations based on Banach contraction principle

Initial value

Dimension 2 × 2

Dimension 10 × 10

Dimension 100 × 100

Dimension 120 × 120

 

\(\theta _{\mathrm{opt}} = 9.8701\text{e-}05\)

\(\theta _{\mathrm{opt}} = 1.6800\text{e-}05\)

\(\theta _{\mathrm{opt}} = 1.4951\text{e-}05\)

\(\theta _{\mathrm{opt}} = 1.4945\text{e-}05\)

 

CT

Error

CT

Error

CT

Error

CT

Error

\(X_{1}\)

3.4340e-04

0.2823

6.1930e-04

0.0934

0.0134

0.1096

0.0236

0.1098

\(X_{2}\)

3.1870e-04

0.2770

3.7480e-04

0.0928

0.0151

0.1095

0.0240

0.1098

\(X_{3}\)

3.0990e-04

0.2610

5.6450e-04

0.0915

0.0143

0.1096

0.0231

0.1099

\(X_{4} \)

3.1040e-04

0.2250

4.5500e-04

0.0925

0.0147

0.1110

0.0228

0.1113

\(X_{5}\)

3.1020e-04

0.2102

3.8710e-04

0.0947

0.0146

0.1120

0.0233

0.1124

\(X_{6}\)

3.1550e-04

0.1867

3.7830e-04

0.1004

0.0145

0.1144

0.0225

0.1149