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  4. Gradient iterative method with optimal convergent factor for solving a generalized sylvester matrix equation with applications to diffusion equations
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Gradient iterative method with optimal convergent factor for solving a generalized sylvester matrix equation with applications to diffusion equations

Author(s)
Boonruangkan, Nunthakarn
Chansangiam, Pattrawut
Date Issued
October 1, 2020
Type
Article
DOI
10.3390/sym12101732
Abstract
We introduce a gradient iterative scheme with an optimal convergent factor for solving a generalized Sylvester matrix equation ∑pi=1A i XBi = F, where Ai, Bi and F are conformable rectangular matrices. The iterative scheme is derived from the gradients of the squared norm-errors of the associated subsystems for the equation. The convergence analysis reveals that the sequence of approximated solutions converge to the exact solution for any initial value if and only if the convergent factor is chosen properly in terms of the spectral radius of the associated iteration matrix. We also discuss the convergent rate and error estimations. Moreover, we determine the fastest convergent factor so that the associated iteration matrix has the smallest spectral radius. Furthermore, we provide numerical examples to illustrate the capability and efficiency of this method. Finally, we apply the proposed scheme to discretized equations for boundary value problems involving convection and diffusion.
Citation
Symmetry, 12(10), 1-14, 2020
Subjects

Convection–diffusion ...

Generalized Sylvester...

Gradient

Linear iterative proc...

Matrix norm

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