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  • Linear systems and matrices

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  • A linear system is equivalent to a vector equation.
  • A linear system is equivalent to a matrix equation.
  • Terminology
  • Using matrices to solve linear systems
  • Matrix equations
  • Row equivalent matrices represent equivalent linear systems
  • Linear systems and echelon matrices

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  • Definition of matrix equation
  • Example of solving a 3-by-3 matrix equation
  • Example of solving a 3-by-3 homogeneous matrix equation
  • A matrix equation is equivalent to a linear system
  • The matrix equation Ax=b has a solution if and only if b is a linear combination of the columns of A.
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Description:Added matrix equations overview
# Matrix equations

Put content here## Matrix Equations
⏎
A matrix equation is an equation of the form `Ax = b`, where `A` is a matrix and `x` and `b` are vectors. Matrix equations provide a compact way to represent and solve systems of linear equations.
⏎
### Key Concepts
- **Matrix multiplication interpretation**: `Ax` is the linear combination of columns of `A` with weights from `x`
- **Existence**: A solution exists when `b` lies in the column space of `A`
- **Uniqueness**: The solution is unique when `A` has full column rank (all columns are pivot columns)
- **Homogeneous case**: `Ax = 0` always has the trivial solution `x = 0`
⏎
### Properties
- If `A` is square and invertible, `Ax = b` has the unique solution `x = A⁻¹b`
- If `A` is not invertible, the system may have no solution or infinitely many solutions
- The set of all solutions to `Ax = 0` forms the null space of `A`
⏎
Matrix equations unify the treatment of linear systems and connect algebraic computation with geometric concepts like span, linear independence, and subspaces.

# Parents

* Linear systems and matrices
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