Minor, cofactor and adjoint matrix

矩阵的余子式、代数余子式与伴随矩阵
这篇博客介绍了线性代数中的余子式、代数余子式(Cofactor)及其在计算行列式和矩阵求逆中的应用。详细讨论了一阶余子式的定义,以及如何通过Cofactor展开计算行列式,并阐述了伴随矩阵(adjoint matrix)在求解矩阵逆时的角色。

1. Minor(余子式)

In linear algebra, a minor of a matrix A is the determinant of some smaller square matrix, cut down from A by removing one or more of its rows or columns.

1.1 First Minor(一阶余子式)

If A is a square matrix, then the minor of the entry in the i-th row and j-th column (also called the (i,j) minor, or a first minor) is the determinant of the submatrix formed by deleting the i-th row and j-th column. This number is often denoted Mij.

For a matrix B ,

B11B21B31B12B22B32B13B23B33

then first minor for B13 is

M13=B21B31B22B32

2.Cofactors(代数余子式)

Cofactors are form first minors, adding (1)i+1 , which are often denoted Cij=(1)1Mij . The cofactor for B is

C13=(1)1+3B21B31B22B32

Cofactors are useful for computing both the determinant and inverse of square matrices.

2.1. Cofactor expansion of the determinant

The determinant of A (denoted det(A)) can be written as the sum of the cofactors of any row or column of the matrix multiplied by the entries that generated them, which is called Laplace expansion or Cofactor expansion

The cofactor expansion along the jth column gives

det(A)=i=1nAijCij

The cofactor expansion along the ith row gives
det(A)=j=1nAijCij

2.2 Cofactor for computing inverse of a matrix

If set cofactor matrix of matrix A as

C=C11C21Cn1C12C22Cn2C1nC2nCnn

which is called adjoint matrix(伴随矩阵)
Then the inverse of A is the transpose of the cofactor matrix times the reciprocal of the determinant of A:

A1=1det(A)CT

proof: from the fact that
AC(A)T=det(A)I

then
A1=1det(A)CT

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