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 an equation. 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.

Rotationmatrix is a kind of matrix, when multiplied by a vector, it has the effect of changing the direction of the vector without changing its size. The rotation matrix does not contain inversion, it can change the right-handed coordinate system into the left-handed coordinate system or vice versa. All rotations are added and inverted to form a set of orthogonal matrices.

The rotation matrix was studied by the world-famous lottery expert and Australian mathematician Dietrov. It can help you lock your favorite number and improve your chances of winning. First, you have to select some numbers, and then, with a certain rotation matrix, fill the numbers you choose in the corresponding positions.

If some of the numbers you choose are the same as the lottery numbers, you are sure to win a prize. Of course, using this rotating matrix, you can get the maximum profit with the minimum cost, and it is far less than the cost of double betting.

Matrix, in mathematics, refers to a two-dimensional data table arranged vertically and horizontally, which originated from a square matrix composed of coefficients and constants of equations. Matrix is a common tool in applied mathematics such as advanced algebra and statistical analysis.

Matrix addition, subtraction, multiplication and other operations are the most basic matrix operations, which conform to general operation rules, such as commutative law and associative law. For example, in computer graphics, matrices can be used to describe positions and directions in three-dimensional space.

In computer vision, matrices can be used to describe the features and shapes of images. In signal processing, matrix can be used to describe the frequency spectrum of the signal and the response of the filter. When solving various problems, it is necessary to master the operation and properties of the matrix and use it flexibly.