Abstract
It is known that among the methods used in solving systems of linear algebraic equations, the Cramer method has a number of disadvantages compared to the Gauss method, in particular: the inability to write out solutions to a system that has many solutions; the cumbersomeness of calculations with large system size. However, when applied to systems with a square matrix, it is, in a sense, more convenient than the Gauss method. The authors of this work developed and proposed a method in which they tried to combine the advantages of the Cramer and Gauss methods. In this paper, the Cramer-Gauss method is adapted to solving systems of linear algebraic equations with three and five-diagonal coefficient matrices and reduced to a form convenient for computer processing. The justification for the relevance of the study is that the approximate solution of a large range of problems, in particular, in the theory of differential equations, is reduced to solving systems of linear algebraic equations with tridiagonal and five-diagonal coefficient matrices.
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Urdaletova, A., Sklyar, S., Kydyraliev, S., Burova, E. (2023). Using the Cramer-Gauss Method to Solve Systems of Linear Algebraic Equations with Tridiagonal and Five-Diagonal Coefficient Matrices. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2022. Lecture Notes in Networks and Systems, vol 544. Springer, Cham. https://doi.org/10.1007/978-3-031-16075-2_31
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DOI: https://doi.org/10.1007/978-3-031-16075-2_31
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