Augmented Matrix: A matrix where each row is an equation, and each column is the coefficients for a particular variable in each equation. For example:
Gaussian Elimination: Using elementary row operations to put a matrix in echelon form
Gauss-Jordan Elimination: Using elementary row operations to put a matrix in reduced echelon form
Reduced Echelon Matrix: A matrix is in reduced row echelon form (also called row canonical form) if it satisfies the following conditions:
- It is in row echelon form.
- The leading entry in each nonzero row is 1 (called a leading one).
- Each column containing a leading 1 has zeros in all its other entries.
Steps: - Make 1
- Make everything below zero
- Repeat with
Free Variable: A variable that can’t be eliminated or constrained. Happens when you have more variables than equations.
Elementary Row Operations
Equivalent to operations on systems
Interchange Equations: Swap two rows
Multiply an Equation by a Constant: Multiply one row by a constant.. Ex:
Add a multiple of one equation to another:
Ex: Row 2 + 2* Row 3 Row 2
Application/Problem Types
Wire Temperature
- Make an equation for each node, temp = average of all connected nodes
- solve for constant
- Put into matrix
- RREF
Balance the Chemical Equation
Traffic Management:
- Write an equation for each intersection (A,B,C) where one side is the sum of all the input and the other is the side of all the output
A: - Solve equations for the constant
- RREF
Find the missing values in the partial fraction decomposition
- Generate a single, distributed equation
- Separate each “set of coefficients” (here it’s constants and coefficients of x, but it could be powers of x or different variables (I think))
- RREF