• 【线性代数基础进阶】矩阵-part1


    一、概念、运算

    概念

    m × n m\times n m×n个数排成如下 m m m n n n列的一个表格
    ( a 11 a 12 ⋯ a 1 n a 21 a 2 2 ⋯ a 2 ⋮ ⋮ ⋮ a m 1 a m 2 ⋯ a m n )

    (a11a12a1na21a22a2am1am2amn)" role="presentation" style="position: relative;">(a11a12a1na21a22a2am1am2amn)
    a11a21am1a12a22am2a1na2amn
    称为一个 m × n m\times n m×n矩阵
    m = n m=n m=n时,称为 n n n阶矩阵或 n n n阶方阵,简记为 A A A

    如果一个矩阵的所有元素都是 0 0 0,即
    ( 0 0 ⋯ 0 0 0 ⋯ 0 ⋮ ⋮ ⋮ 0 0 ⋯ 0 )

    (000000000)" role="presentation" style="position: relative;">(000000000)
    000000000
    称这个矩阵为零矩阵,简记 O O O

    如果 A A A B B B都是 m × n m\times n m×n矩阵,称为 A A A B B B是同型矩阵
    A A A B B B都是 m × n m\times n m×n矩阵,如果
    a i j = b i j ( ∀ i = 1 , 2 , ⋯   , m ; j = 1 , 2 , ⋯   , n ) a_{ij}=b_{ij}\quad(\forall i=1,2,\cdots,m;j=1,2,\cdots,n) aij=bij(i=1,2,,m;j=1,2,,n)
    称矩阵 A A A B B B相等,记作 A = B A=B A=B

    一个矩阵主对角元素的和叫际

    运算

    加法

    同型矩阵可以做加法
    A + B = ( a i j + b i j ) A+B=(a_{ij}+b_{ij}) A+B=(aij+bij)

    加法运算法则( A , B , C A,B,C A,B,C同型)

    • A + B = B + A A+B=B+A A+B=B+A
    • ( A + B ) + C = A + ( B + C ) = A + B + C (A+B)+C=A+(B+C)=A+B+C (A+B)+C=A+(B+C)=A+B+C
    • A + O = O + A = A A+O=O+A=A A+O=O+A=A
    • A + ( − A ) = O A+(-A)=O A+(A)=O

    数乘

    数乘,注意不要和行列式混
    k A = ( k a i j ) kA=(ka_{ij}) kA=(kaij)

    数乘运算法则

    • k ( m A ) = m ( k A ) = ( k m ) A k(mA)=m(kA)=(km)A k(mA)=m(kA)=(km)A
    • ( k + m ) A = k A + m A (k+m)A=kA+mA (k+m)A=kA+mA
    • k ( A + B ) = k A + k B k(A+B)=kA+kB k(A+B)=kA+kB
    • 1 A = A , 0 A = O 1A=A,0A=O 1A=A,0A=O

    乘法

    A = ( a i j ) m × s , B = ( b i j ) s × n A B = C = ( c i j ) m × n c i j = a i 1 b 1 j + a i 2 b 2 j + ⋯ + a i s b s j = ∑ k = 1 s a i k b k j

    A=(aij)m×s,B=(bij)s×nAB=C=(cij)m×ncij=ai1b1j+ai2b2j++aisbsj=k=1saikbkj" role="presentation" style="position: relative;">A=(aij)m×s,B=(bij)s×nAB=C=(cij)m×ncij=ai1b1j+ai2b2j++aisbsj=k=1saikbkj
    A=(aij)m×s,B=(bij)s×nAB=C=(cij)m×ncij=ai1b1j+ai2b2j++aisbsj=k=1saikbkj

    注意

    1. A B ≠ B A AB\ne BA AB=BA
    2. A B = O ⇏ A = O 或 B = O AB=O\nRightarrow A=O或B=O AB=OA=OB=O
    3. A B = A C , A ≠ O ⇏ B = C AB=AC,A\ne O\nRightarrow B=C AB=AC,A=OB=C

    对于向量,行在前列在后,乘出来是数;行在后列在前,乘出来是方阵

    转置

    A = ( a i j ) m × n A=(a_{ij})_{m\times n} A=(aij)m×n,将 A A A和行、列互换,得到的 n × m n\times m n×m的矩阵 ( a j i ) n × m (a_{ji})_{n\times m} (aji)n×m称为 A A A的转置矩阵,记为 A T A^{T} AT

    转置运算法则:

    • ( A + B ) T = A T + B T (A+B)^{T}=A^{T}+B^{T} (A+B)T=AT+BT
    • ( k A ) T = k A T (kA)^{T}=kA^{T} (kA)T=kAT
    • ( A B ) T = B T A T (AB)^{T}=B^{T}A^{T} (AB)T=BTAT
    • ( A T ) T = A (A^{T})^{T}=A (AT)T=A

    对角矩阵

    Λ = ( λ 1 0 ⋯ 0 0 λ 2 ⋯ 0 ⋮ ⋮ ⋮ 0 0 ⋯ λ n ) \Lambda=

    (λ1000λ2000λn)" role="presentation" style="position: relative;">(λ1000λ2000λn)
    Λ= λ1000λ2000λn
    这个方阵的特点是:不在对角线上的元素都是 0 0 0,我们把这种方阵称为对角矩阵,简称对角阵,对角阵也记作 Λ = d i a g ( λ 1 , λ 2 , ⋯   , λ n ) \Lambda=diag(\lambda_1,\lambda_2,\cdots,\lambda_n) Λ=diag(λ1,λ2,,λn)

    d i a g ( a 1 , a 2 , ⋯   , a n ) d i a g ( b 1 , b 2 , ⋯   , b n ) = d i a g ( a 1 b 1 , a 2 b 2 , ⋯   , a n b n ) diag(a_{1},a_{2},\cdots,a_{n})diag(b_{1},b_{2},\cdots,b_{n})=diag(a_{1}b_{1},a_{2}b_{2},\cdots,a_{n}b_{n}) diag(a1,a2,,an)diag(b1,b2,,bn)=diag(a1b1,a2b2,,anbn)

    运算法则

    • Λ 1 Λ 2 = Λ 2 Λ 1 \Lambda_{1}\Lambda_{2}=\Lambda_{2}\Lambda_{1} Λ1Λ2=Λ2Λ1
    • d i a g ( a 1 , a 2 , ⋯   , a n ) k = d i a g ( a 1 k , a 2 k , ⋯   , a n k ) diag(a_{1},a_{2},\cdots,a_{n})^{k}=diag(a_{1}^{k},a_{2}^{k},\cdots,a_{n}^{k}) diag(a1,a2,,an)k=diag(a1k,a2k,,ank)
    • d i a g ( a 1 , a 2 , ⋯   , a n ) d i a g ( 1 a 1 , 1 a 2 , ⋯   , 1 a n ) = d i a g ( 1 , 1 , ⋯   , 1 ) diag(a_{1},a_{2},\cdots,a_{n})diag(\frac{1}{a_{1}},\frac{1}{a_{2}},\cdots, \frac{1}{a_{n}})=diag(1,1,\cdots,1) diag(a1,a2,,an)diag(a11,a21,,an1)=diag(1,1,,1)
      d i a g ( a 1 , a 2 , ⋯   , a n ) − 1 = d i a g ( 1 a 1 , 1 a 2 , ⋯   , 1 a n ) diag(a_{1},a_{2},\cdots,a_{n})^{-1}=diag(\frac{1}{a_{1}},\frac{1}{a_{2}},\cdots, \frac{1}{a_{n}}) diag(a1,a2,,an)1=diag(a11,a21,,an1)

    例:设 α = ( 2 3 1 ) T , β = ( 3 − 1 2 ) T \alpha=

    (231)" role="presentation" style="position: relative;">(231)
    ^{T},\beta=
    (312)" role="presentation" style="position: relative;">(312)
    ^{T} α=(231)T,β=(312)T

    α β T = ( 6 − 2 4 9 − 3 6 3 − 1 2 ) β α T = ( 6 9 3 − 2 − 3 − 1 4 6 2 ) α T β = 5 β T α = 5 α β T , β α T , α T β , β T α 的迹相等 α α T = ( 4 6 2 4 9 3 2 3 1 ) 是对称矩阵 α T α = 2 2 + 3 2 + 1 2 = 14 是个元素的平方和

    αβT=(624936312)βαT=(693231462)αTβ=5βTα=5αβT,βαT,αTβ,βTαααT=(462493231)αTα=22+32+12=14" role="presentation" style="position: relative;">αβT=(624936312)βαT=(693231462)αTβ=5βTα=5αβT,βαT,αTβ,βTαααT=(462493231)αTα=22+32+12=14
    αβTβαTαTββTαααTαTα= 693231462 = 624936312 =5=5αβT,βαT,αTβ,βTα的迹相等= 442693231 是对称矩阵=22+32+12=14是个元素的平方和

    例:
    { x 1 + 2 x 2 − x 3 + 4 x 4 = 2 2 x 1 − x 2 + x 3 + x 4 = 1 x 1 + 7 x 2 − 4 x 3 + 11 x 4 = 5

    {x1+2x2x3+4x4=22x1x2+x3+x4=1x1+7x24x3+11x4=5" role="presentation" style="position: relative;">{x1+2x2x3+4x4=22x1x2+x3+x4=1x1+7x24x3+11x4=5
    x1+2x2x3+4x4=22x1x2+x3+x4=1x1+7x24x3+11x4=5
    可表示为
    ( 1 2 − 1 4 2 − 1 1 1 1 7 − 4 11 ) ( x 1 x 2 x 3 x 4 ) = ( 2 1 5 )
    (1214211117411)" role="presentation" style="position: relative;">(1214211117411)
    (x1x2x3x4)" role="presentation" style="position: relative;">(x1x2x3x4)
    =
    (215)" role="presentation" style="position: relative;">(215)
    1212171144111 x1x2x3x4 = 215

    记作
    A x = b Ax=b Ax=b
    向量表示
    ( α 1 α 2 α 3 α 4 ) ( x 1 x 2 x 3 x 4 ) = b
    (α1α2α3α4)" role="presentation" style="position: relative;">(α1α2α3α4)
    (x1x2x3x4)" role="presentation" style="position: relative;">(x1x2x3x4)
    =b
    (α1α2α3α4) x1x2x3x4 =b


    x 1 α 1 + x 2 α 2 + x 3 α 3 + x 4 α 4 = b x_{1}\alpha_{1}+x_{2}\alpha_{2}+x_{3}\alpha_{3}+x_{4}\alpha_{4}=b x1α1+x2α2+x3α3+x4α4=b

    例: α = ( 1 , 2 , 3 ) , β = ( 1 , 1 2 , 1 3 ) , A = α T β \alpha=(1,2,3),\beta=(1,\frac{1}{2},\frac{1}{3}),A=\alpha^{T}\beta α=(1,2,3),β=(1,21,31),A=αTβ,则 A n = ( ) A^{n}=() An=()

    有行有列相乘中间有数

    A n = ( α T β ) ( α T β ) ⋯ ( α T β ) = α T ( β α T ) ( β α T ) ⋯ ( β α T ) β = 3 n − 1 α T β = 3 n − 1 ( 1 1 2 1 3 2 1 2 3 3 3 2 1 )

    An=(αTβ)(αTβ)(αTβ)=αT(βαT)(βαT)(βαT)β=3n1αTβ=3n1(1121321233321)" role="presentation" style="position: relative;">An=(αTβ)(αTβ)(αTβ)=αT(βαT)(βαT)(βαT)β=3n1αTβ=3n1(1121321233321)
    An=(αTβ)(αTβ)(αTβ)=αT(βαT)(βαT)(βαT)β=3n1αTβ=3n1 1232112331321

    例:设 A = E − ξ ξ T A=E-\xi \xi^{T} A=EξξT,其中 ξ \xi ξ n n n为非 0 0 0列向量,证明: A 2 = A ⇔ ξ T ξ = 1 A^{2}=A\Leftrightarrow \xi^{T}\xi=1 A2=AξTξ=1

    A 2 = ( E − ξ ξ T ) ( E − ξ ξ T ) = ( E − ξ ξ T ) − ξ ξ T + ξ ξ T ξ ξ T = A + ( ξ T ξ − 1 ) ξ ξ T

    A2=(EξξT)(EξξT)=(EξξT)ξξT+ξξTξξT=A+(ξTξ1)ξξT" role="presentation" style="position: relative;">A2=(EξξT)(EξξT)=(EξξT)ξξT+ξξTξξT=A+(ξTξ1)ξξT
    A2=(EξξT)(EξξT)=(EξξT)ξξT+ξξTξξT=A+(ξTξ1)ξξT
    由于 ξ ≠ 0 \xi\ne0 ξ=0,则 ξ ξ T ≠ 0 \xi \xi^{T}\ne0 ξξT=0
    A 2 = A ⇔ ( ξ T ξ − 1 ) ξ ξ T = 0 ⇔ ξ T ξ − 1 = 0 ⇔ ξ T ξ = 1
    A2=A(ξTξ1)ξξT=0ξTξ1=0ξTξ=1" role="presentation" style="position: relative;">A2=A(ξTξ1)ξξT=0ξTξ1=0ξTξ=1
    A2=A(ξTξ1)ξξT=0ξTξ1=0ξTξ=1

    二、伴随矩阵、可逆矩阵

    伴随矩阵

    A A A的伴随矩阵 A ∗ A^{*} A
    A ∗ = ( A 11 A 21 ⋯ A n 1 A 12 A 22 ⋯ A n 2 ⋮ ⋮ ⋮ A 1 n A 2 n ⋯ A n n ) , 其中 A i j = ( − 1 ) i + j M i j A^{*}=

    (A11A21An1A12A22An2A1nA2nAnn)" role="presentation" style="position: relative;">(A11A21An1A12A22An2A1nA2nAnn)
    ,其中A_{ij}=(-1)^{i+j}M_{ij} A= A11A12A1nA21A22A2nAn1An2Ann ,其中Aij=(1)i+jMij

    例:求 A = ( a b c d ) A=

    (abcd)" role="presentation" style="position: relative;">(abcd)
    A=(acbd)的伴随矩阵

    A 11 = d , A 12 = − c , A 21 = − b , A 22 = a A_{11}=d,A_{12}=-c,A_{21}=-b,A_{22}=a A11=d,A12=c,A21=b,A22=a

    ( a b c d ) ∗ = ( d − b − c a )

    (abcd)" role="presentation" style="position: relative;">(abcd)
    ^{*}=
    (dbca)" role="presentation" style="position: relative;">(dbca)
    (acbd)=(dcba)

    主对角线互换,副对角线变号

    伴随矩阵的公式

    • A A ∗ = A ∗ A = ∣ A ∣ E AA^{*}=A^{*}A=|A|E AA=AA=AE
      A A ∗ = ( a 11 a 12 a 21 a 22 ) ( A 11 A 21 A 12 A 22 ) = ( a 11 A 11 + a 12 A 12 a 11 A 21 + a 12 A 22 a 21 A 11 + a 22 A 12 a 21 A 21 + a 22 A 22 ) = ( ∣ A ∣ 0 0 ∣ A ∣ ) = ∣ A ∣ ( 1 0 0 1 )
      AA=(a11a12a21a22)(A11A21A12A22)=(a11A11+a12A12a11A21+a12A22a21A11+a22A12a21A21+a22A22)=(|A|00|A|)=|A|(1001)" role="presentation" style="position: relative;">AA=(a11a12a21a22)(A11A21A12A22)=(a11A11+a12A12a11A21+a12A22a21A11+a22A12a21A21+a22A22)=(|A|00|A|)=|A|(1001)
      AA=(a11a21a12a22)(A11A12A21A22)=(a11A11+a12A12a21A11+a22A12a11A21+a12A22a21A21+a22A22)=(A00A)=A(1001)

      A − 1 = 1 ∣ A ∣ A ∗ , A ∗ = ∣ A ∣ A − 1 A^{-1}=\frac{1}{|A|}A^{*},A^{*}=|A|A^{-1} A1=A1A,A=AA1,其实是由上式移项出来的
    • ( k A ) ∗ = k n − 1 A ∗ (kA)^{*}=k^{n-1}A^{*} (kA)=kn1A
    • ( A ∗ ) T = ( A T ) ∗ (A^{*})^{T}=(A^{T})^{*} (A)T=(AT)
    • ∣ A ∗ ∣ = ∣ A ∣ n − 1 |A^{*}|=|A|^{n-1} A=An1
    • ( A ∗ ) ∗ = ∣ A ∣ n − 2 A (A^{*})^{*}=|A|^{n-2}A (A)=An2A
    • ( A ∗ ) − 1 = ( A − 1 ) ∗ = 1 ∣ A ∣ A (A^{*})^{-1}=(A^{-1})^{*}=\frac{1}{|A|}A (A)1=(A1)=A1A

    可逆矩阵

    对于 n n n阶矩阵 A A A,如果存在 n n n阶矩阵 B B B使
    A B = B A = E AB=BA=E AB=BA=E
    则称矩阵 A A A是可逆的,称 B B B A A A的逆矩阵

    结论:如果矩阵 A A A是可逆的,那么 A A A的逆矩阵是唯一的,记作 A − 1 A^{-1} A1
    证明:设 B , C B,C B,C都是 A A A的逆矩阵,即
    A B = B A = E , A C = C A = E AB=BA=E,AC=CA=E AB=BA=E,AC=CA=E

    B = B E = B ( A C ) = ( B A ) C = E C = C B=BE=B(AC)=(BA)C=EC=C B=BE=B(AC)=(BA)C=EC=C
    证毕

    定理: A A A可逆 ⇔ ∣ A ∣ ≠ 0 \Leftrightarrow|A|\ne0 A=0

    推论: A , B A,B A,B n n n阶矩阵,如 A B = E AB=E AB=E,则 A − 1 = B A^{-1}=B A1=B
    证明:
    A B = E AB=E AB=E

    ∣ A ∣ ⋅ ∣ B ∣ = ∣ E ∣ = 1 ≠ 0 |A|\cdot|B|=|E|=1\ne0 AB=E=1=0
    所以 A A A可逆
    B A = E B A = ( A − 1 A ) B A = A − 1 ( A B ) A = A − 1 E A = E BA=EBA=(A^{-1}A)BA=A^{-1}(AB)A=A^{-1}EA=E BA=EBA=(A1A)BA=A1(AB)A=A1EA=E
    所以 A − 1 = B A^{-1}=B A1=B

    逆矩阵的性质

    • 如果 A A A可逆,则 A − 1 A^{-1} A1也可逆,且 ( A − 1 ) − 1 = A (A^{-1})^{-1}=A (A1)1=A
    • 如果 A A A可逆,且 k ≠ 0 k\ne0 k=0,则 k A kA kA可逆,且 ( k A ) − 1 = 1 k A − 1 (kA)^{-1}=\frac{1}{k}A^{-1} (kA)1=k1A1
    • 如果 A , B A,B A,B均可逆,则 A B AB AB也可逆,且 ( A B ) − 1 = B − 1 A − 1 (AB)^{-1}=B^{-1}A^{-1} (AB)1=B1A1
      推广 A B C = C − 1 B − 1 A − 1 ABC=C^{-1}B^{-1}A^{-1} ABC=C1B1A1
    • 如果 A A A可逆,则 A T A^{T} AT也可逆,且 ( A T ) − 1 = ( A − 1 ) T (A^{T})^{-1}=(A^{-1})^{T} (AT)1=(A1)T

    求逆矩阵方法

    • 定义法: A B = E AB=E AB=E
    • 用伴随(常用于二阶矩阵,三阶也行): A − 1 = 1 ∣ A ∣ A ∗ A^{-1}=\frac{1}{|A|}A^{*} A1=A1A
    • 初等行变换: ( A ∣ E ) ⟶ 由上往下 ( 上三角矩阵 ∣ 矩阵 ) ⟶ 由下往上 ( 对角矩阵 ∣ 矩阵 ) → ( E ∣ A − 1 ) (A|E)\overset{由上往下}{\longrightarrow}(上三角矩阵|矩阵)\overset{由下往上}{\longrightarrow}(对角矩阵|矩阵)\rightarrow(E|A^{-1}) (AE)由上往下(上三角矩阵矩阵)由下往上(对角矩阵矩阵)(EA1)
    • 分块: ( A O O B ) − 1 = ( A − 1 O O B − 1 ) ( O A B O ) − 1 = ( O B − 1 A − 1 O )
      (AOOB)" role="presentation" style="position: relative;">(AOOB)
      ^{-1}=
      (A1OOB1)" role="presentation" style="position: relative;">(A1OOB1)
      \quad
      (OABO)" role="presentation" style="position: relative;">(OABO)
      ^{-1}=
      (OB1A1O)" role="presentation" style="position: relative;">(OB1A1O)
      (AOOB)1=(A1OOB1)(OBAO)1=(OA1B1O)

    例:设 A = ( 1 2 3 2 2 1 3 4 3 ) A=

    (123221343)" role="presentation" style="position: relative;">(123221343)
    A= 123224313 ,求 A − 1 A^{-1} A1

    ( A ∣ E ) = ( 1 2 3 1 0 0 2 2 1 0 1 0 3 4 3 0 0 1 ) → ( 1 2 3 1 0 0 0 − 2 − 5 − 2 1 0 0 − 2 − 6 − 3 0 1 ) → ( 1 2 3 1 0 0 0 − 2 − 5 − 2 1 0 0 0 − 1 − 1 − 1 1 ) → ( 1 2 0 − 2 − 3 3 0 − 2 0 3 6 − 5 0 0 − 1 − 1 − 1 1 ) → ( 1 0 0 1 3 − 2 0 − 2 0 3 6 − 5 0 0 − 1 − 1 − 1 1 ) → ( 1 0 0 1 3 − 2 0 1 0 − 3 2 − 3 5 2 0 0 1 1 1 − 1 )

    (A|E)=(123100221010343001)(123100025210026301)(123100025210001111)(120233020365001111)(100132020365001111)(10013201032352001111)" role="presentation" style="position: relative;">(A|E)=(123100221010343001)(123100025210026301)(123100025210001111)(120233020365001111)(100132020365001111)(10013201032352001111)
    (AE)= 123224313100010001 100222356123010001 100220351121011001 100220001231361351 100020001131361251 10001000112313312251

    例: A A A n n n阶方阵,满足 A 2 − 3 A − 2 E = 0 A^{2}-3A-2E=0 A23A2E=0,表示 A − 1 , ( A + E ) − 1 A^{-1},(A+E)^{-1} A1,(A+E)1

    求谁的逆由谁出发,构造题中给出的等式,移项使得构造出的等式右端为 E E E,此时左端应为谁乘一个矩阵,该矩阵记为所求
    在构造矩阵的时候,先降次构造不全为 E E E的部分, E E E用来补全等式

    A ( A − 3 E ) − 2 E = 0  先构造带有 A 2 的部分,然后补全 A E ,最后补 E A ⋅ 1 2 ( A − 3 E ) = E

    A(A3E)2E=0 A2AEEA12(A3E)=E" role="presentation" style="position: relative;">A(A3E)2E=0 A2AEEA12(A3E)=E
    A(A3E)2EA21(A3E)=E=0 先构造带有A2的部分,然后补全AE,最后补E
    显然 A − 1 = 1 2 ( A − 3 E ) A^{-1}=\frac{1}{2}(A-3E) A1=21(A3E)
    ( A + E ) ( A − 4 E ) + 2 E = 0  依旧是先构造带有 A 2 的部分,然后补全 A E 注意此处构造出 ( A + E ) ( A ⋯   ) 时,式子乘开已经含有一个 A E 因此接下来构造 A E 需要 − 4 A E 即 − 4 E 最后整个乘开看和题中等式差几个 E ,补上 ( A + E ) ⋅ 1 2 ( 4 E − A ) = E
    (A+E)(A4E)+2E=0 A2AE(A+E)(A)AEAE4AE4EE(A+E)12(4EA)=E" role="presentation" style="position: relative;">(A+E)(A4E)+2E=0 A2AE(A+E)(A)AEAE4AE4EE(A+E)12(4EA)=E
    (A+E)(A4E)+2E=0 依旧是先构造带有A2的部分,然后补全AE注意此处构造出(A+E)(A)时,式子乘开已经含有一个AE因此接下来构造AE需要4AE4E最后整个乘开看和题中等式差几个E,补上(A+E)21(4EA)=E

    显然 ( A + E ) − 1 = 1 2 ( 4 E − A ) (A+E)^{-1}=\frac{1}{2}(4E-A) (A+E)1=21(4EA)

    例:已知 A = ( 1 0 0 1 1 0 1 1 1 ) , B = ( 0 1 1 1 0 1 1 1 0 ) A=

    (100110111)" role="presentation" style="position: relative;">(100110111)
    ,B=
    (011101110)" role="presentation" style="position: relative;">(011101110)
    A= 111011001 ,B= 011101110 ,且 A X A + B X B = A X B + B X A + E AXA+BXB=AXB+BXA+E AXA+BXB=AXB+BXA+E,则 X = ( ) X=() X=()

    A X A + B X B − A X B − B X A = E A X ( A − B ) + B X ( B − A ) = E ( A − B ) X ( A − B ) = E X = ( A − B ) − 1 E ( A − B ) − 1 X = [ ( A − B ) − 1 ] 2 = [ ( 1 − 1 − 1 0 1 − 1 0 0 1 ) − 1 ] 2 = ( 1 1 2 0 1 1 0 0 1 ) 2 = ( 1 2 5 0 1 2 0 0 1 )

    AXA+BXBAXBBXA=EAX(AB)+BX(BA)=E(AB)X(AB)=EX=(AB)1E(AB)1X=[(AB)1]2=[(111011001)1]2=(112011001)2=(125012001)" role="presentation" style="position: relative;">AXA+BXBAXBBXA=EAX(AB)+BX(BA)=E(AB)X(AB)=EX=(AB)1E(AB)1X=[(AB)1]2=[(111011001)1]2=(112011001)2=(125012001)
    AXA+BXBAXBBXAAX(AB)+BX(BA)(AB)X(AB)XX=E=E=E=(AB)1E(AB)1=[(AB)1]2=[ 100110111 1]2= 100110211 2= 100210521

    例: A A A n n n阶矩阵,存在自然数 k k k,使得 A k = O A^{k}=O Ak=O,证明 E − A E-A EA可逆并求其逆

    思路同上面构造逆矩阵
    注意构造的矩阵是为了构造不含 E E E的部分

    A k = O A^{k}=O Ak=O,有
    ( E − A ) ( E + A + A 2 + ⋯ + A k − 1 ) − E = − A k = O (E-A)(E+A+A^{2}+\cdots+A^{k-1})-E=-A^{k}=O (EA)(E+A+A2++Ak1)E=Ak=O

    ( E − A ) ( E + A + A 2 + ⋯ + A k − 1 ) = E

    (EA)(E+A+A2++Ak1)=E" role="presentation" style="position: relative;">(EA)(E+A+A2++Ak1)=E
    (EA)(E+A+A2++Ak1)=E
    因此 E − A E-A EA可逆,显然 ( E − A ) − 1 = E + A + A 2 + ⋯ + A k − 1 (E-A)^{-1}=E+A+A^{2}+\cdots+A^{k-1} (EA)1=E+A+A2++Ak1

    活动地址:CSDN21天学习挑战赛

  • 相关阅读:
    程序员缺乏经验的 7 种表现,你中了几个?
    IO流中「线程」模型总结
    LVGL---对象(lv_obj_t)
    Spring架构浅析
    2022.11.3 英语背诵
    剑指JUC原理-5.synchronized底层原理
    poj 1742 coins
    OSPF原理
    Linux学习6—文件的查找与压缩
    机器学习理论基础—支持向量机的推导(一)
  • 原文地址:https://blog.csdn.net/liu20020918zz/article/details/126366526