矩阵的向量化及内积

定义1. 设矩阵 A = ( a i j ) R m × n \boldsymbol{A} = (a_{ij})\in R^{m\times n} , 把矩阵 A \boldsymbol{A} 的元素按行的顺序排列成一个列向量:
v e c A = ( a 11 , a 12 , , a 1 n , a 21 , a 22 , , a 2 n , , a m 1 , a m 2 , , a m n ) T vec\boldsymbol{A} = (a_{11},a_{12},\cdot\cdot\cdot,a_{1n},a_{21},a_{22},\cdot\cdot\cdot,a_{2n},\cdot\cdot\cdot,a_{m1},a_{m2},\cdot\cdot\cdot,a_{mn})^T

则称向量 v e c A vec\boldsymbol{A} 为矩阵 A \boldsymbol{A} 按行展开的列向量。

定义2. 设矩阵 A = ( a i j ) R m × n \boldsymbol{A} = (a_{ij})\in R^{m\times n} , 把矩阵 A \boldsymbol{A} 的元素按列的顺序排列成一个列向量:
v e c A = ( a 11 , a 21 , , a n 1 , a 12 , a 22 , , a n 2 , , a 1 m , a 2 m , , a n m ) T vec\boldsymbol{A} = (a_{11},a_{21},\cdot\cdot\cdot,a_{n1},a_{12},a_{22},\cdot\cdot\cdot,a_{n2},\cdot\cdot\cdot,a_{1m},a_{2m},\cdot\cdot\cdot,a_{nm})^T

则称向量 v e c A vec\boldsymbol{A} 为矩阵 A \boldsymbol{A} 按列展开的列向量。

定义3. A , B R n × n \boldsymbol{A,B}\in R^{n\times n} ,称
A B = < A , B > = T r ( A T B ) = i = 1 n j = 1 n a i j b i j = ( v e c A ) T v e c B \boldsymbol{A\cdot B} = <\boldsymbol{A,B}>=Tr(\boldsymbol{A^TB})=\sum\limits_{i=1}^n \sum\limits_{j=1}^n a_{ij}b_{ij}=(vec\boldsymbol{A})^Tvec\boldsymbol{B}

为矩阵 A , B \boldsymbol{A,B} 的内积。其中, T r a c e ( A ) Trace(\boldsymbol{A}) 为矩阵 A \boldsymbol{A} 的迹,简记为 T r ( A ) Tr(\boldsymbol{A})

以上内容编辑:崔健棣

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转载自blog.csdn.net/DoctorCuiLab/article/details/83243845