矩阵理论复习部分——线性代数(2)矩阵运算

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一、矩阵类型

1、转置矩阵:



A

=

(

3

2

1

1

2

3

2

3

1

)

A = \begin{pmatrix} 3 & 2 & 1 \\ 1 & 2 & 3 \\ 2 & 3 & 1 \\ \end{pmatrix}






A




=































































3








1








2





























2








2








3





























1








3








1







































































A

T

=

(

3

1

2

2

2

3

1

3

1

)

A^T = \begin{pmatrix} 3 & 1 & 2 \\ 2 & 2 & 3 \\ 1 & 3 & 1 \\ \end{pmatrix}







A










T











=































































3








2








1





























1








2








3





























2








3








1








































































T

T






T





表示矩阵的转置

2、对角矩阵:



(

2

0

0

0

3

0

0

0

1

)

\begin{pmatrix} 2 & 0 & 0 \\ 0 & 3 & 0 \\ 0 & 0 & 1 \\ \end{pmatrix}





























































2








0








0





























0








3








0





























0








0








1





































































对角矩阵(diagonal matrix)是一个主对角线之外的元素皆为0的矩阵,常写为



d

i

a

g

(

a

1

,

a

2

,

a

3

,

.

.

.

,

a

n

)

\mathrm{diag}(a_1,a_2,a_3,…,a_n)







diag



(



a










1


















,





a










2


















,





a










3


















,







,





a










n


















)





3、上下三角矩阵:



(

1

2

3

0

2

3

0

0

1

)

\begin{pmatrix} 1 & 2 & 3 \\ 0 & 2 & 3 \\ 0 & 0 & 1 \\ \end{pmatrix}





























































1








0








0





























2








2








0





























3








3








1







































































(

1

0

0

3

2

0

2

3

1

)

\begin{pmatrix} 1 & 0 & 0 \\ 3 & 2 & 0 \\ 2 & 3 & 1 \\ \end{pmatrix}





























































1








3








2





























0








2








3





























0








0








1


































































4、单位矩阵:



(

1

0

0

0

1

0

0

0

1

)

=

E

=

I

\begin{pmatrix} 1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \\ \end{pmatrix} = E = I





























































1








0








0





























0








1








0





























0








0








1


































































=








E




=








I




5、

正交矩阵:若



n

n






n





阶方阵



A

A






A





,满足



A

A

T

=

E

AA^T=E






A



A










T











=








E





,称



A

A






A





为正交矩阵

6、

对称矩阵:



A

T

=

T

A^T=T







A










T











=








T







二、矩阵的基本运算

1、加法、减法:矩阵对应元素位置直接进行加减法运算,矩阵形状不发生改变;

2、乘法:左行乘右列(矩阵能够进行乘法的前提是:矩阵的左行等于右列);



三、矩阵运算相关性质


矩阵运算不一定满足交换律:



A

B

B

A

AB \not= BA






A


B



























=








B


A






数乘分配律:





(

λ

+

μ

)

A

=

λ

A

+

μ

A

(\lambda + \mu)A = \lambda A + \mu A






(


λ




+








μ


)


A




=








λ


A




+








μ


A







λ

(

A

+

B

)

=

λ

A

+

λ

B

\lambda(A+ B) = \lambda A + \lambda B






λ


(


A




+








B


)




=








λ


A




+








λ


B





矩阵分配律:





(

A

B

)

C

=

A

(

B

C

)

(AB)C = A(BC)






(


A


B


)


C




=








A


(


BC


)







A

(

B

+

C

)

A

B

+

A

C

A(B+C) AB + AC






A


(


B




+








C


)


A


B




+








A


C







(

B

+

C

)

A

=

B

A

+

C

A

(B + C)A = BA + CA






(


B




+








C


)


A




=








B


A




+








C


A







E

A

=

A

E

=

A

EA =AE =A






E


A




=








A


E




=








A





转置相关性质:





(

A

T

)

T

=

A

(A^T)^T = A






(



A










T










)










T











=








A







(

A

+

B

)

T

=

A

T

+

B

T

(A + B)^T = A^T + B^T






(


A




+








B



)










T











=









A










T











+









B










T














(

A

B

)

T

=

B

T

A

T

(AB)^T = B^TA^T






(


A


B



)










T











=









B










T










A










T













(有些特殊)


模的性质:





A

B

=

A

B

|A \cdot B| = |A| \cdot |B|









A













B







=











A



















B










λ

A

=

λ

n

A

|\lambda A| = \lambda^n|A|









λ


A







=









λ










n












A












n

n






n





为矩阵



A

A






A





的阶数)



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