2022International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021)Requires access

Study about three methods of solving linear equations

Yichen Zhou

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Abstract

Since linear equations have great contribution in the study of the numerical pde, therefore it has been studied for ages. In this paper, I will write a survey that contains three methods of solving the linear equations, as well as the implementations of these three methods. After that, other methods of finding the inverse matrix of a specific sparse matrix will be shown. Three methods are the Gauss elimination, LU decomposition and Cholesky decomposition. These algorithms can be implemented by invoking related built-in functions in MATLAB. The LU decomposition, as a method of decomposing a matrix into an upper triangular matrix and a lower triangular matrix, can be performed by calling the function lu() in MATLAB. Cholesky factorization can be achieved by calling the function chol() in MATLAB.

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What this paper is about

Since linear equations have great contribution in the study of the numerical pde, therefore it has been studied for ages. In this paper, I will write a survey that contains three methods of solving the linear equations, as well as the implementations of these three methods. After that, other methods of finding the inverse matrix of a specific sparse matrix will be shown. Three methods are the Gauss elimination, LU decomposition and Cholesky decomposition. These algorithms can be implemented by invoking related built-in functions in MATLAB. The LU decomposition, as a method of decomposing a matrix into an upper triangular matrix and a lower triangular matrix, can be performed by calling the function lu() in MATLAB. Cholesky factorization can be achieved by calling the function chol() in MATLAB.

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Available abstract

Since linear equations have great contribution in the study of the numerical pde, therefore it has been studied for ages. In this paper, I will write a survey that contains three methods of solving the linear equations, as well as the implementations of these three methods. After that, other methods of finding the inverse matrix of a specific sparse matrix will be shown. Three methods are the Gauss elimination, LU decomposition and Cholesky decomposition. These algorithms can be implemented by invoking related built-in functions in MATLAB. The LU decomposition, as a method of decomposing a matrix into an upper triangular matrix and a lower triangular matrix, can be performed by calling the function lu() in MATLAB. Cholesky factorization can be achieved by calling the function chol() in MATLAB.

Key concepts: Cholesky decomposition, LU decomposition, Gaussian elimination, Incomplete Cholesky factorization, Matrix decomposition, MATLAB, Triangular matrix, Matrix (chemical analysis)

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