• 【线性代数基础进阶】矩阵-part2


    三、初等变换、初等矩阵

    矩阵的初等行变换

    • 用非 0 0 0常数 k k k A A A某行的每个元素,即倍乘
    • 互换 A A A中两行元素的位置,即互换
    • A A A中某行所有元素的 k k k倍加到另一行的对应元上,即倍加

    初等矩阵

    单位矩阵经过一次初等变换所得到的矩阵称为初等矩阵

    初等矩阵 P P P左乘矩阵 A A A,其乘积 P A PA PA就是矩阵 A A A作一次与 P P P同样的行变换
    初等矩阵 P P P右乘矩阵 A A A,其乘积 A P AP AP就是矩阵 A A A作一次与 P P P同样的列变换

    初等矩阵的逆

    ( 1 0 0 2 1 0 0 0 1 ) ( 1 0 0 − 2 1 0 0 0 1 ) = ( 1 0 0 0 1 0 0 0 1 )

    (100210001)" role="presentation" style="position: relative;">(100210001)
    (100210001)" role="presentation" style="position: relative;">(100210001)
    =
    (100010001)" role="presentation" style="position: relative;">(100010001)
    120010001 120010001 = 100010001
    初等矩阵若为倍加矩阵,则其逆矩阵为将其倍加的元改为其相反数,例如
    ( 1 0 0 2 1 0 0 0 1 ) − 1 = ( 1 0 0 − 2 1 0 0 0 1 )
    (100210001)" role="presentation" style="position: relative;">(100210001)
    ^{-1}=
    (100210001)" role="presentation" style="position: relative;">(100210001)
    120010001 1= 120010001

    ( 0 1 0 1 0 0 0 0 1 ) ( 0 1 0 1 0 0 0 0 1 ) = ( 1 0 0 0 1 0 0 0 1 )

    (010100001)" role="presentation" style="position: relative;">(010100001)
    (010100001)" role="presentation" style="position: relative;">(010100001)
    =
    (100010001)" role="presentation" style="position: relative;">(100010001)
    010100001 010100001 = 100010001
    初等矩阵若为互换矩阵,则其逆矩阵为本身,例如
    ( 0 1 0 1 0 0 0 0 1 ) − 1 = ( 0 1 0 1 0 0 0 0 1 )
    (010100001)" role="presentation" style="position: relative;">(010100001)
    ^{-1}=
    (010100001)" role="presentation" style="position: relative;">(010100001)
    010100001 1= 010100001

    ( 1 0 0 0 5 0 0 0 1 ) ( 1 0 0 0 1 5 0 0 0 1 ) = ( 1 0 0 0 1 0 0 0 1 )

    (100050001)" role="presentation" style="position: relative;">(100050001)
    (1000150001)" role="presentation" style="position: relative;">(1000150001)
    =
    (100010001)" role="presentation" style="position: relative;">(100010001)
    100050001 1000510001 = 100010001
    初等矩阵若为倍乘矩阵,则其逆矩阵为倍乘的元的倒数,例如
    ( 1 0 0 0 5 0 0 0 1 ) − 1 = ( 1 0 0 0 1 5 0 0 0 1 )
    (100050001)" role="presentation" style="position: relative;">(100050001)
    ^{-1}=
    (1000150001)" role="presentation" style="position: relative;">(1000150001)
    100050001 1= 1000510001

    初等矩阵均可逆,且其逆是同一类型的初等矩阵

    例:已知 a i j ≠ 0 a_{ij}\ne0 aij=0,如果 ( a 11 a 12 a 13 a 21 a 22 a 23 a 31 a 32 a 33 ) P = ( a 11 2 a 12 a 12 + a 13 a 11 a 21 a 22 a 22 + a 23 a 11 a 31 a 32 a 32 + a 33 )

    (a11a12a13a21a22a23a31a32a33)" role="presentation" style="position: relative;">(a11a12a13a21a22a23a31a32a33)
    P=
    (a112a12a12+a13a11a21a22a22+a23a11a31a32a32+a33)" role="presentation" style="position: relative;">(a112a12a12+a13a11a21a22a22+a23a11a31a32a32+a33)
    a11a21a31a12a22a32a13a23a33 P= a112a11a21a11a31a12a22a32a12+a13a22+a23a32+a33 ,则 P = ( ) P=() P=()

    经过第一列乘 a 11 a_{11} a11倍,第三列加第二列,因此
    P = ( a 11 0 0 0 1 1 0 0 1 ) P=

    (a1100011001)" role="presentation" style="position: relative;">(a1100011001)
    P= a1100010011

    例:已知 A = ( a i j ) A=(a_{ij}) A=(aij)是三阶矩阵, ∣ A ∣ = 2 |A|=2 A=2,把矩阵 A A A的第二行的 − 5 -5 5倍加到第三行得到矩阵 B B B,则 ( 3 B A ∗ ) − 1 = ( ) (3BA^{*})^{-1}=() (3BA)1=()

    由题意 B = P A B=PA B=PA,且
    P = ( 1 0 0 0 1 0 0 − 5 1 ) P=

    (100010051)" role="presentation" style="position: relative;">(100010051)
    P= 100015001

    3 B A ∗ = 3 P A A ∗ = 3 P ( ∣ A ∣ E ) = 6 P 3BA^{*}=3PAA^{*}=3P(|A|E)=6P 3BA=3PAA=3P(AE)=6P

    ( 3 B A ∗ ) − 1 = ( 6 P ) − 1 = 1 6 P − 1 = 1 6 ( 1 0 0 0 1 0 0 5 1 ) (3BA^{*})^{-1}=(6P)^{-1}=\frac{1}{6}P^{-1}=\frac{1}{6}
    (100010051)" role="presentation" style="position: relative;">(100010051)
    (3BA)1=(6P)1=61P1=61 100015001

    行阶梯矩阵

    A A A m × n m\times n m×n矩阵,若满足

    • 矩阵如有零行,则零行都在矩阵的底部
    • 每个非零行的主元(即该行最左边的第 1 1 1个非 0 0 0元)所在列的下面的元素都是 0 0 0

    则称 A A A为行阶梯矩阵

    行最简矩阵

    A A A m × n m\times n m×n矩阵,若 A A A是行阶梯矩阵,且还满足

    • 非零行的主元都是 1 1 1,且主元所在列的其他元素都是 0 0 0

    则称 A A A为行最简矩阵

    矩阵等价

    矩阵 A A A经过有限次初等变换得到矩阵 B B B就称矩阵 A A A与矩阵 B B B等价,记作 A = ∼ B A\overset{\sim}{=}B A=B

    矩阵 A , B A,B A,B都是 m × n m\times n m×n的矩阵,则 A , B A,B A,B等价 ⇔ r ( A ) = r ( B ) \Leftrightarrow r(A)=r(B) r(A)=r(B)

    A A A m × n m\times n m×n矩阵,则存在 m m m姐可逆矩阵 P P P n n n阶可逆矩阵 A A A,使
    P A Q = ( E r O O O ) PAQ=

    (ErOOO)" role="presentation" style="position: relative;">(ErOOO)
    PAQ=(ErOOO)

    例:已知 A = ( 1 − 1 − 1 3 2 − 1 − 3 1 3 2 − 5 2 ) A=

    (111321313252)" role="presentation" style="position: relative;">(111321313252)
    A= 123112135312 化其为行最简

    A = ( 1 − 1 − 1 3 2 − 1 − 3 1 3 2 − 5 2 ) → ( 1 − 1 − 1 3 0 1 − 1 − 5 0 5 − 2 − 7 ) → ( 1 0 − 2 − 2 0 1 − 1 − 5 0 0 3 18 ) 从左到右各列上下同时开工 → ( 1 0 − 2 − 2 0 1 − 1 − 5 0 0 1 6 ) 如果第一个非零元不是 1 ,先化成 1 → ( 1 0 0 10 0 1 0 1 0 0 1 6 )

    A=(111321313252)(111301150527)(1022011500318)(102201150016)11(1001001010016)" role="presentation" style="position: relative;">A=(111321313252)(111301150527)(1022011500318)(102201150016)11(1001001010016)
    A= 123112135312 100115112357 1000102132518 从左到右各列上下同时开工 100010211256 如果第一个非零元不是1,先化成1 1000100011016

    对于已知 P A = B , A , B PA=B,A,B PA=B,A,B,求 P P P的题
    已知
    A ⟶ 行变换 B A\overset{行变换}{\longrightarrow}B A行变换B
    即存在
    P τ ⋯ P 2 P 1 A = B P_{\tau}\cdots P_{2}P_{1}A=B PτP2P1A=B
    P = P τ ⋯ P 2 P 1 P=P_{\tau}\cdots P_{2}P_{1} P=PτP2P1
    P τ ⋯ P 2 P 1 E = P P_{\tau}\cdots P_{2}P_{1}E=P PτP2P1E=P
    A → B A\rightarrow B AB同时 E → P E\rightarrow P EP
    ( A , E ) ⟶ 行变换 ( B , P ) (A,E)\overset{行变换}{\longrightarrow}(B,P) (A,E)行变换(B,P)

    对于上一道例题,要求使得 A A A变为行最简的 P P P

    ( A ∣ E ) = ( 1 − 1 − 1 3 1 2 − 1 − 3 1 1 3 2 − 5 2 1 ) → ( 1 − 1 − 1 3 1 0 1 − 1 − 5 − 2 1 0 5 − 2 − 7 − 3 1 ) → ( 1 − 1 − 1 3 1 0 1 − 1 − 5 − 2 1 0 0 3 18 7 − 5 1 ) → ( 1 0 − 2 − 2 − 1 1 1 − 1 − 5 − 2 1 1 6 7 3 − 5 3 1 3 ) → ( 1 0 0 10 11 3 − 7 3 2 3 0 1 0 1 1 3 − 2 3 1 3 0 0 1 6 7 3 − 5 3 1 3 )

    (A|E)=(111312131132521)(11131011521052731)(1113101152100318751)(1022111152116735313)(10010113732301011323130016735313)" role="presentation" style="position: relative;">(A|E)=(111312131132521)(11131011521052731)(1113101152100318751)(1022111152116735313)(10010113732301011323130016735313)
    (AE)= 123112135312111 10011511235712311 1001101133518127151 1012112561237113531 10001000110163113137373235323131

    四、分块矩阵

    分四块( A B , A n , A − 1 AB,A^{n},A^{-1} AB,An,A1),列分块、行分块(方程组的解,向量,阶)

    分四块

    对矩阵适当的分块处理,有以下的运算法则
    ( A 1 A 2 A 3 A 4 ) + ( B 1 B 2 B 3 B 4 ) = ( A 1 + B 1 A 2 + B 2 A 3 + B 3 A 4 + B 4 ) ( A B C D ) ( X Y Z W ) = ( A X + B Z A Y + B W C X + D Z C Y + D W ) ( A B C D ) T = ( A T C T B T D T )

    (A1A2A3A4)+(B1B2B3B4)=(A1+B1A2+B2A3+B3A4+B4)(ABCD)(XYZW)=(AX+BZAY+BWCX+DZCY+DW)(ABCD)T=(ATCTBTDT)" role="presentation" style="position: relative;">(A1A2A3A4)+(B1B2B3B4)=(A1+B1A2+B2A3+B3A4+B4)(ABCD)(XYZW)=(AX+BZAY+BWCX+DZCY+DW)(ABCD)T=(ATCTBTDT)
    (A1A3A2A4)+(B1B3B2B4)=(A1+B1A3+B3A2+B2A4+B4)(ACBD)(XZYW)=(AX+BZCX+DZAY+BWCY+DW)(ACBD)T=(ATBTCTDT)
    如果 B , C B,C B,C都是方阵
    ( B O O C ) n = ( B n O O C n )
    (BOOC)" role="presentation" style="position: relative;">(BOOC)
    ^{n}=
    (BnOOCn)" role="presentation" style="position: relative;">(BnOOCn)
    (BOOC)n=(BnOOCn)

    如果 B , C B,C B,C是可逆方阵
    ( B O O C ) − 1 = ( B − 1 O O C − 1 ) , ( O B C O ) − 1 = ( O C − 1 B − 1 O )
    (BOOC)" role="presentation" style="position: relative;">(BOOC)
    ^{-1}=
    (B1OOC1)" role="presentation" style="position: relative;">(B1OOC1)
    ,
    (OBCO)" role="presentation" style="position: relative;">(OBCO)
    ^{-1}=
    (OC1B1O)" role="presentation" style="position: relative;">(OC1B1O)
    (BOOC)1=(B1OOC1),(OCBO)1=(OB1C1O)

    行、列分块

    A B = C AB=C AB=C
    ( γ 1 γ 2 γ 3 ) ( b 11 b 12 b 13 b 21 b 22 b 23 b 31 b 32 b 33 ) = ( δ 1 δ 2 δ 3 )

    (γ1γ2γ3)" role="presentation" style="position: relative;">(γ1γ2γ3)
    (b11b12b13b21b22b23b31b32b33)" role="presentation" style="position: relative;">(b11b12b13b21b22b23b31b32b33)
    =
    (δ1δ2δ3)" role="presentation" style="position: relative;">(δ1δ2δ3)
    (γ1γ2γ3) b11b21b31b12b22b32b13b23b33 =(δ1δ2δ3)
    对应行列式
    { b 11 γ 1 + b 21 γ 2 + b 31 γ 3 = δ 1 b 12 γ 1 + b 22 γ 2 + b 32 γ 3 = δ 2 b 13 γ 1 + b 23 γ 2 + b 33 γ 3 = δ 3
    {b11γ1+b21γ2+b31γ3=δ1b12γ1+b22γ2+b32γ3=δ2b13γ1+b23γ2+b33γ3=δ3" role="presentation" style="position: relative;">{b11γ1+b21γ2+b31γ3=δ1b12γ1+b22γ2+b32γ3=δ2b13γ1+b23γ2+b33γ3=δ3
    b11γ1+b21γ2+b31γ3=δ1b12γ1+b22γ2+b32γ3=δ2b13γ1+b23γ2+b33γ3=δ3

    C = A B C=AB C=AB的列向量可由 A A A的列向量线性表出
    同理
    ( a 11 a 12 a 13 a 21 a 22 a 23 a 31 a 32 a 33 ) ( α 1 α 2 α 3 ) = ( β 1 β 2 β 3 )
    (a11a12a13a21a22a23a31a32a33)" role="presentation" style="position: relative;">(a11a12a13a21a22a23a31a32a33)
    (α1α2α3)" role="presentation" style="position: relative;">(α1α2α3)
    =
    (β1β2β3)" role="presentation" style="position: relative;">(β1β2β3)
    a11a21a31a12a22a32a13a23a33 α1α2α3 = β1β2β3

    对应行列式
    { a 11 α 1 + a 12 α 2 + a 13 α 3 = β 1 a 21 α 1 + a 22 α 2 + a 23 α 3 = β 2 a 31 α 1 + a 32 α 2 + a 33 α 3 = β 3
    {a11α1+a12α2+a13α3=β1a21α1+a22α2+a23α3=β2a31α1+a32α2+a33α3=β3" role="presentation" style="position: relative;">{a11α1+a12α2+a13α3=β1a21α1+a22α2+a23α3=β2a31α1+a32α2+a33α3=β3
    a11α1+a12α2+a13α3=β1a21α1+a22α2+a23α3=β2a31α1+a32α2+a33α3=β3

    C = A B C=AB C=AB的行向量可由 B B B的行向量线性表出

    如果 A A A可逆, A B = C → A − 1 C = B AB=C\rightarrow A^{-1}C=B AB=CA1C=B
    B B B的行向量可由 C C C的行向量线性表出
    如果 B B B可逆, A B = C → C B − 1 = A AB=C\rightarrow CB^{-1}=A AB=CCB1=A
    A A A的列向量可由 C C C的列向量线性表出

    如果 A B = C AB=C AB=C
    A ( β 1 β 2 β 3 ) = ( γ 1 γ 2 γ 3 ) ( A β 1 A β 2 A β 3 ) = ( γ 1 γ 2 γ 3 )

    A(β1β2β3)=(γ1γ2γ3)(Aβ1Aβ2Aβ3)=(γ1γ2γ3)" role="presentation" style="position: relative;">A(β1β2β3)=(γ1γ2γ3)(Aβ1Aβ2Aβ3)=(γ1γ2γ3)
    A(β1β2β3)(Aβ1Aβ2Aβ3)=(γ1γ2γ3)=(γ1γ2γ3)

    A β 1 = γ 1 , A β 2 = γ 2 , A β 3 = γ 3 A \beta_{1}=\gamma_{1},A \beta_{2}=\gamma_{2},A \beta_{3}=\gamma_{3} Aβ1=γ1,Aβ2=γ2,Aβ3=γ3
    可知
    β 1 \beta_{1} β1是方程组 A x = γ 1 Ax=\gamma_{1} Ax=γ1的解
    β 2 \beta_{2} β2是方程组 A x = γ 2 Ax=\gamma_{2} Ax=γ2的解
    β 3 \beta_{3} β3是方程组 A x = γ 3 Ax=\gamma_{3} Ax=γ3的解

    如果 A B = O AB=O AB=O
    A ( β 1 β 2 β 3 ) = ( O O O a ) A

    (β1β2β3)" role="presentation" style="position: relative;">(β1β2β3)
    =
    (OOOa)" role="presentation" style="position: relative;">(OOOa)
    A(β1β2β3)=(OOOa)
    可知 β 1 , β 2 , β 3 \beta_{1},\beta_{2},\beta_{3} β1,β2,β3 A x = O Ax=O Ax=O的解

    例:已知 X = A B A X=ABA X=ABA,其中 A = ( 1 0 0 1 0 1 1 0 0 1 − 1 0 1 0 0 − 1 ) , B = ( 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 ) A=

    (1001011001101001)" role="presentation" style="position: relative;">(1001011001101001)
    ,B=
    (0001001001001000)" role="presentation" style="position: relative;">(0001001001001000)
    A= 1001011001101001 ,B= 0001001001001000 ,则 X = ( ) X=() X=()

    本题直接求也行

    A = ( 1 0 0 1 0 1 1 0 0 1 − 1 0 1 0 0 − 1 ) = ( E C C − E ) , B = ( 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 ) = ( O C C O ) A=\left(

    1001011001101001" role="presentation" style="position: relative;">1001011001101001
    \right)=
    (ECCE)" role="presentation" style="position: relative;">(ECCE)
    ,B=\left(
    0001001001001000" role="presentation" style="position: relative;">0001001001001000
    \right)=
    (OCCO)" role="presentation" style="position: relative;">(OCCO)
    A= 1001011001101001 =(ECCE),B= 0001001001001000 =(OCCO)

    X = ( E C C − E ) ( O C C O ) ( E C C − E ) = ( E C − C E ) ( E C C − E ) = ( 2 E O O − 2 E )
    X=(ECCE)(OCCO)(ECCE)=(ECCE)(ECCE)=(2EOO2E)" role="presentation" style="position: relative;">X=(ECCE)(OCCO)(ECCE)=(ECCE)(ECCE)=(2EOO2E)
    X=(ECCE)(OCCO)(ECCE)=(ECCE)(ECCE)=(2EOO2E)

    可得 X = ( 2 2 − 2 − 2 ) X=
    (2222)" role="presentation" style="position: relative;">(2222)
    X= 2222

    例:设 A = ( 1 2 − 2 4 t 3 3 − 1 1 ) A=

    (1224t3311)" role="presentation" style="position: relative;">(1224t3311)
    A= 1432t1231 B B B为三阶非零矩阵,且 A B = O AB=O AB=O,则 t = ( ) t=() t=()

    由于 A B = O AB=O AB=O
    A B = A ( β 1 β 2 β 3 ) = ( A β 1 A β 2 A β 3 ) = ( O O O ) AB=A

    (β1β2β3)" role="presentation" style="position: relative;">(β1β2β3)
    =
    (Aβ1Aβ2Aβ3)" role="presentation" style="position: relative;">(Aβ1Aβ2Aβ3)
    =
    (OOO)" role="presentation" style="position: relative;">(OOO)
    AB=A(β1β2β3)=(Aβ1Aβ2Aβ3)=(OOO)
    可知 A β 1 = O , A β 2 = O , A β 3 = O A \beta_{1}=O,A \beta_{2}=O,A \beta_{3}=O Aβ1=O,Aβ2=O,Aβ3=O
    因此, β 1 , β 2 , β 3 \beta_{1},\beta_{2},\beta_{3} β1,β2,β3 A X = O AX=O AX=O的解
    又因为 B ≠ 0 B\ne0 B=0,故 A X = O AX=O AX=O存在非 0 0 0解,根据克拉默法则
    ∣ A ∣ = ∣ 1 2 − 2 4 t 3 3 − 1 1 ∣ = 5 ( t + 3 ) = 0 |A|=
    |1224t3311|" role="presentation" style="position: relative;">|1224t3311|
    =5(t+3)=0
    A= 1432t1231 =5(t+3)=0

    解得 t = − 3 t=-3 t=3

    例:计算 ( 1 2 3 4 5 6 7 8 9 ) ( 2 0 0 0 1 − 1 1 0 1 )

    (123456789)" role="presentation" style="position: relative;">(123456789)
    (200011101)" role="presentation" style="position: relative;">(200011101)
    147258369 201010011

    简单的矩阵乘复杂的矩阵,可以考虑复杂的进行分块,复杂的在左面进行列分块,在右面进行行分块

    原式 = ( α 1 α 2 α 3 ) ( 2 0 0 0 1 − 1 1 0 1 ) = ( 2 α 1 + α 3 α 2 − α 2 + α 3 ) = ( 5 2 1 14 5 1 23 8 1 )

    =(α1α2α3)(200011101)=(2α1+α3α2α2+α3)=(52114512381)" role="presentation" style="position: relative;">=(α1α2α3)(200011101)=(2α1+α3α2α2+α3)=(52114512381)
    原式=(α1α2α3) 201010011 =(2α1+α3α2α2+α3)= 51423258111

    五、方阵的行列式

    • ∣ A T ∣ = ∣ A ∣ |A^{T}|=|A| AT=A
    • ∣ k A ∣ = k n ∣ A ∣ |kA|=k^{n}|A| kA=knA
    • ∣ A B ∣ = ∣ A ∣ ⋅ ∣ B ∣ |AB|=|A|\cdot|B| AB=AB
      ∣ A 2 ∣ = ∣ A ∣ 2 |A^{2}|=|A|^{2} A2=A2
    • ∣ A ∗ ∣ = ∣ A ∣ n − 1 |A^{*}|=|A|^{n-1} A=An1
    • ∣ A − 1 ∣ = ∣ A ∣ − 1 = 1 ∣ A ∣ |A^{-1}|=|A|^{-1}=\frac{1}{|A|} A1=A1=A1
    • ∣ A O ∗ B ∣ = ∣ A ∗ O B ∣ = ∣ A ∣ ⋅ ∣ B ∣
      |AOB|" role="presentation" style="position: relative;">|AOB|
      =
      |AOB|" role="presentation" style="position: relative;">|AOB|
      =|A|\cdot|B|
      AOB = AOB =AB

      ∣ O A B ∗ ∣ = ∣ ∗ A B O ∣ = ( − 1 ) m n ∣ A ∣ ⋅ ∣ B ∣
      |OAB|" role="presentation" style="position: relative;">|OAB|
      =
      |ABO|" role="presentation" style="position: relative;">|ABO|
      =(-1)^{mn}|A|\cdot|B|
      OBA = BAO =(1)mnAB
    • 如果 A ∼ B A\sim B AB,则 ∣ A ∣ = ∣ B ∣ , ∣ A + k E ∣ = ∣ B + k E ∣ |A|=|B|,|A+kE|=|B+kE| A=B,A+kE=B+kE,一般 ∣ A + B ∣ ≠ ∣ A ∣ + ∣ B ∣ |A+B|\ne|A|+|B| A+B=A+B

    例: A , B A,B A,B n n n阶矩阵, ∣ A ∣ = 2 , ∣ B ∣ = − 3 |A|=2,|B|=-3 A=2,B=3,则

    ∣ A ∗ B − 1 − A − 1 B ∗ ∣ = ( ) |A^{*}B^{-1}-A^{-1}B^{*}|=() AB1A1B=()
    ∣ A ∗ B − 1 − A − 1 B ∗ ∣ = ∣ ∣ A ∣ A − 1 B − 1 − ∣ B ∣ A − 1 B − 1 ∣ = ∣ 5 A − 1 B − 1 ∣ = − 5 n 6

    |AB1A1B|=||A|A1B1|B|A1B1|=|5A1B1|=5n6" role="presentation" style="position: relative;">|AB1A1B|=||A|A1B1|B|A1B1|=|5A1B1|=5n6
    AB1A1B=∣∣AA1B1BA1B1=∣5A1B1=65n

    ∣ O A T B ∗ 2 B ∣ = ( )

    |OATB2B|" role="presentation" style="position: relative;">|OATB2B|
    =() OBAT2B =()
    ∣ O A T B ∗ 2 B ∣ = ( − 1 ) n ⋅ n ∣ A T ∣ ∣ B ∗ ∣ = ( − 1 ) n 2 + n − 1 ⋅ 2 ⋅ 3 n − 1 = − 2 ⋅ 3 n − 1
    |OATB2B|=(1)nn|AT||B|=(1)n2+n123n1=23n1" role="presentation" style="position: relative;">|OATB2B|=(1)nn|AT||B|=(1)n2+n123n1=23n1
    OBAT2B =(1)nnAT∣∣B=(1)n2+n123n1=23n1

  • 相关阅读:
    ShardingSphere实现读写分离
    智慧中控屏
    PCL 点云添加标签属性并将带标签的点云保存成文件
    免费的中英文翻译软件-自动批量中英文翻译软件推荐大全
    【推荐】10款最好用的下载工具
    MySQL(二):表的增删改查
    grpc、https、oauth2等认证专栏实战11:授权码模式介绍
    oracle-long类型转clob类型及clob类型字段的导出导入
    程序员的情人节「GitHub 热点速览 v.22.07」
    Windows 10驱动开发入门(四):USB下的过滤器驱动
  • 原文地址:https://blog.csdn.net/liu20020918zz/article/details/126366615