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:

  1. It is in row echelon form.
  2. The leading entry in each nonzero row is 1 (called a leading one).
  3. Each column containing a leading 1 has zeros in all its other entries.
    Steps:
  4. Make 1
  5. Make everything below zero
  6. 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

  1. Make an equation for each node, temp = average of all connected nodes
  2. solve for constant
  3. Put into matrix
  4. RREF

Balance the Chemical Equation

Traffic Management:

  1. 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:
  2. Solve equations for the constant
  3. RREF

Find the missing values in the partial fraction decomposition

  1. Generate a single, distributed equation
  2. 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))
  3. RREF