Conjugate Gradient Algorithm for Least-Squares Solutions of a Generalized Sylvester-Transpose Matrix Equation
نویسندگان
چکیده
We derive a conjugate-gradient type algorithm to produce approximate least-squares (LS) solutions for an inconsistent generalized Sylvester-transpose matrix equation. The is always applicable any given initial and will arrive at LS solution within finite steps. When the equation has many solutions, can search one with minimal Frobenius-norm. Moreover, Y, find unique closest Y. Numerical experiments show relevance of square/non-square dense/sparse matrices medium/large sizes. works well in both number iterations computation time, compared direct Kronecker linearization well-known iterative methods.
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ژورنال
عنوان ژورنال: Symmetry
سال: 2022
ISSN: ['0865-4824', '2226-1877']
DOI: https://doi.org/10.3390/sym14091868