In fact, the division of computing matrix is to transform the partitioned matrix into its inverse matrix, which is equivalent to one-third of the partitioned matrix, so the division of matrix is equivalent to the product of the inverse matrix of the previous matrix and the latter matrix.

1. To calculate the division of a matrix, first convert the division matrix into its inverse matrix, and then multiply the previous matrix by the inverse matrix of the next matrix.

2. Then, the solution of the inverse matrix of a matrix is: first, put a identity matrix on the right side of the target matrix, and then transform the matrix on the left into identity matrix through elementary row transformation, and the matrix on the right is the inverse matrix we require.

3. Here is an example to illustrate the specific calculation method of matrix division.

4. First, put identity matrix on the right of matrix A and put it in the same matrix. At present, the second line and the third line subtract 3 times and-1 times from the first line respectively.

5. First, add 2/5 times of the second line with the first line and the third line respectively. Then add 1/9 times and-1/5 times of the third line to the first and second lines respectively.

6. Finally, the final result can be obtained by multiplying matrix B by the inverse matrix of matrix A, that is, dividing matrix B by matrix A. ..

In mathematics, a matrix is a group of complex numbers or real numbers arranged in a rectangular array, which originated from a square matrix composed of coefficients and constants of equations. This concept was first put forward by British mathematician Kelly in19th century.

Matrix is a common tool in applied mathematics such as advanced algebra and statistical analysis.

In physics, matrices have applications in circuit science, mechanics, optics and quantum physics. In computer science, three-dimensional animation also needs matrix. Matrix operation is an important problem in the field of numerical analysis. Decomposition of a matrix into a combination of simple matrices can simplify the operation of the matrix in theory and practical application. For some widely used and special matrices, such as sparse matrix and quasi-diagonal matrix, there are concrete fast operation algorithms. For the development and application of matrix related theory, please refer to matrix theory. Infinite-dimensional matrices will also appear in astrophysics, quantum mechanics and other fields, which is the generalization of matrices.