Matrix multiplication is an operation in linear algebra and is used in mathematics, physics, engineering, computer science, and data analytics. Reasons for using matrix multiplication include:
- Linear equations: Solve systems of linear equations.
- Linear transformations: Perform linear transformations to rotate, scale, or translate two-dimensional or three-dimensional images.
- Eigenvectors and eigenvalues: Calculate eigenvectors and eigenvalues used in quantum mechanics, cryptography, and network analysis.
- Data analytics: Perform clustering, classification, and dimensionality reduction.
- Machine learning: Perform machine learning algorithms for neural networks, support vector machines, and principal component analysis.
TD_MATRIXMULTIPLY takes two source matrixes as input. This function enables you to create a data series by performing a matrix multiplication (the dot product) of the two source matrixes. The first matrix referenced in the function call is referred to as primary matrix The second matrix referenced is referred to as secondary matrix. For the multiplication to be successful, the number of matrix columns in the primary matrix must be the same as the number of rows in the secondary matrix.