Image and Kernel 值域和核

Image / 值域

Definition / 定义

The image (or range) of a linear transformation is the set of all vectors that can be written as for some .

线性变换 的值域(或范围)是所有可以写成 形式的 中的向量 的集合,其中

Properties / 性质

  • The dimension of the image of is equal to the rank of the matrix . 的值域的维度等于矩阵 的秩。
  • The image is a subspace of . 值域是 的子空间。

Kernel / 核

Definition / 定义

The kernel (or null space) of a linear transformation is the set of all vectors that are mapped to the zero vector in , i.e., .

线性变换 的核(或零空间)是所有被映射到 中的零向量的 中的向量 的集合,即

Properties / 性质

  • The dimension of the kernel of is called the nullity of . 的核的维度称为 的零度。
  • The kernel is a subspace of . 核是 的子空间。

Relationship between Image and Kernel / 值域和核的关系

Rank-Nullity Theorem / 秩-零度定理

For a linear transformation , the sum of the dimension of the image (rank) and the dimension of the kernel (nullity) is equal to the dimension of the domain :

对于线性变换 ,值域的维度(秩)和核的维度(零度)的和等于定义域 的维度: