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Then, the alternating-direction Sinc-Galerkin (ADSG) method is applied for solving this matrix equation.
For solving this matrix equation we will use the same method as for Example 3.1.
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The partial least squares (PLS) method was used to solve this matrix.
There are several methods that can be used to solve this matrix including simply solving for each of these coefficients or using methods such as the Levinson, Wiggins, and Robertson's method or Morf's method [31], used for this analysis.
The main purpose of this study is to evaluate the efficiency of a class of incomplete LU (ILU) factorization preconditioners for solving this type of matrices.
For solving this drawback, researchers use random matrix theory to study cross correlation properties of stock.
This work focuses on efficient strategies for solving the matrix systems that result from discretization and linearization of the governing equations.
In this section, we give another example by solving the matrix case problem (5) for comparison with the MM method.
According to Theorem 3, a memorial controller can be obtained by solving the matrix inequality (17).
According to Theorem 2, a controller can be obtained by solving the matrix inequality (13).
In this case, how to restore the original data is among the practical difficulties faced when solving the matrix reconstruction problem.
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