Matrix multiplication is the process of multiplying two matrices. If the number of columns in the first matrix is equal to the number of rows in the second matrix, then the two matrices can be multiplied. There are many calculation methods of matrix multiplication, among which the most commonly used is the "dot product" method. Specifically, for two n×m matrices A and B, their product AB can be calculated by the following formula:

$$

AB = begin { b matrix } a _ { 1 1 } b _ { 1 1 } & amp； a _ { 12 } b _ { 2 1 } & amp； cdots & ampa _ { 1n } b _ { n 1 } a _ { 2 1 } b _ { 1 1 } & amp； a _ { 22 } b _ { 2 1 } & amp； cdots & ampa _ { 2n } b _ { n 1 } vdots & amp； vdots & ampddots & ampvdo TSA _ { n 1 } b _ { 1 1 } & amp； a _ { N2 } b _ { 2 1 } & amp； cdots & ampa_{nn}b_{nn}end{bmatrix}

$$

Where $a_{ij}$ represents the element in row I and column J, and $b_{ij}$ represents the element in row J and column I. The meaning of this formula is to multiply the elements in the corresponding positions of row I of A and column J of B, and then add the results to get the value in the corresponding position in AB.

If you want to calculate the matrix multiplication manually, you can use the "dot product" method mentioned above. If you want to use computer programs to calculate, you can use libraries or tools provided by various programming languages to achieve it. For example, in Python, you can use the NumPy library for matrix calculation.