- When Gaussian Elimination Breaks Down
- The Inverse Matrix
- Let and assume that completes with a matrix that has no zero elements on its diagonal.
- has a unique solution.
- Let be a permutation vector. Then is said to be a permutation matrix.
If is a permutation matrix, then so is .
- Swap the th row with the th.
- Permutation matrices, when applied from the left, swap rows.
- Permutation matrices, when applied from the right, swap columns.
- Solving then changes to
- Compute such that .
- Update .
- Solve (forward substitution)
- Solve (backward substitution)
- maps a rea to a real and it is a bijection(both one-to-one and onto)
- bijection means: every element in R, there is a unique output in R.
- has a unique solution for all .
- The function that maps y to x so that is called the inverse of .
- It is denoted by .
- If and , then , where is the th column of B and is the th unit basis vector.
Assume A, B, and C are square matrices that are nonsingular. Then
The following statements are equivalent statements about :
- A is nonsingular(不可逆).
- A is invertible.
- undoes what matrix A did.
- Identity Matrix
- A represents a linear transformation that is a bijection.
- Ax = b has a unique solution for all .
- implies that .
- has a solution for all .
- The determinant of A is nonzero: .
Theorem: Let be a permutation matrix. Then .
- permutation [,pə:mju:'teiʃən] n. [数] 排列；[数] 置换
- bijection [bai'dʒekʃən] n. [数] 双射
- determinant [di'tə:minənt] adj. 决定性的 n. 决定因素；[数] 行列式