# Operator Descriptions (tables)

Each operator in this section is explained with the operations of scalars, vectors, and matrices that are allowed for said operator.

Each operator in this section is explained with the operations of scalars, vectors, and matrices that are allowed for said operator.

**Addition**

The table below describes the Addition operator.**Colon**

The colon operator has a number before and after it.**Complex Transpose**

Complex Transpose is different from transpose in that any complex numbers are also conjugated.**Inequality Operators**

All inequality operators return logical values (either 0/false or 1/true).**Left Division**

This type of division is different from Left Matrix Division in that the division is performed on each pair of corresponding elements.**Left Matrix Division**

Left Matrix Division (A\B) is defined as solving the equation Ax = B.**Logical Operators (tables)**

All inequality operators return logical values (either 0/false or 1/true).**Matrix Multiplication**

Matrix Multiplication is defined as the multiplication of two matrices.**Matrix Power**

Power means multiplying something by itself a specific number of times. Likewise for matrix power.**Multiplication**

This type of multiplication is different from Matrix Multiplication in that the multiplication is performed on each pair of corresponding elements.**Power**

This type of power is different from Matrix Power in that the power (multiplication of something by itself) is done through each corresponding element.**Right Division**

This type of division is different from Right Matrix Division in that the division is performed on each pair of corresponding elements.**Right Matrix Division**

Right Matrix Division (B/A) is defined as solving the equation xA = B.**Short Circuit**

Short Circuit includes && (short circuit and) and || (short circuit or). They are both logical operators.**Subtraction**

The table below describes the Subtraction operator.**Transpose**

The transpose of a matrix is also a matrix. The rows of the transpose are the columns of the original matrix and vice-versa.