南航双语矩阵论第三章部分题解

南航矩阵论课后习题答案南航矩阵论课后习题答案矩阵论是数学中的一个重要分支，广泛应用于各个领域，包括物理学、工程学、计算机科学等等。

南航的矩阵论课程是培养学生数学思维和解决实际问题的重要环节。

在课后习题中，学生需要运用所学的矩阵理论知识，解答各种问题。

下面是南航矩阵论课后习题的一些答案和解析。

1. 已知矩阵A = [1 2 3; 4 5 6; 7 8 9]，求A的逆矩阵。

解析：要求一个矩阵的逆矩阵，需要先判断该矩阵是否可逆。

一个矩阵可逆的充要条件是其行列式不为零。

计算矩阵A的行列式，得到det(A) = -3。

因此，矩阵A可逆。

接下来，我们可以使用伴随矩阵法求解逆矩阵。

首先，计算矩阵A的伴随矩阵Adj(A)，然后将其除以行列式的值，即可得到逆矩阵。

计算得到A的伴随矩阵为Adj(A) = [-3 6 -3; 6 -12 6; -3 6 -3]。

最后，将伴随矩阵除以行列式的值，即可得到矩阵A的逆矩阵A^-1 = [-1 2 -1; 2 -4 2; -1 2 -1]。

2. 已知矩阵A = [2 1; 3 4]，求A的特征值和特征向量。

解析：要求一个矩阵的特征值和特征向量，需要先求解其特征方程。

特征方程的形式为|A - λI| = 0，其中A为给定矩阵，λ为特征值，I为单位矩阵。

计算得到特征方程为|(2-λ) 1; 3 (4-λ)| = (2-λ)(4-λ) - 3 = λ^2 - 6λ + 5 = 0。

解这个二次方程，得到特征值λ1 = 1，λ2 = 5。

接下来，我们可以求解对应于每个特征值的特征向量。

将特征值代入(A - λI)x = 0，即可求解出特征向量。

对于特征值λ1 = 1，解得特征向量x1 = [1; -1]；对于特征值λ2 = 5，解得特征向量x2 = [1; 3]。

3. 已知矩阵A = [1 2; 3 4]，求A的奇异值分解。

解析：奇异值分解是将一个矩阵分解为三个矩阵的乘积：A = UΣV^T，其中U和V是正交矩阵，Σ是对角矩阵。

《矩阵论》复习提纲与习题选讲Chapter1 线性空间和内积空间内容总结：z 线性空间的定义、基和维数；z 一个向量在一组基下的坐标；z 线性子空间的定义与判断；z 子空间的交z 内积的定义；z 内积空间的定义；z 向量的长度、距离和正交的概念；z Gram-Schmidt 标准正交化过程；z 标准正交基。

习题选讲：1、设表示实数域3]x [R R 上次数小于3的多项式再添上零多项式构成 的线性空间（按通常多项式的加法和数与多项式的乘法）。

（1） 求的维数；并写出的一组基；求在所取基下的坐标；3]x [R 3]x [R 221x x ++ （2） 在中定义3]x [R ， ∫−=11)()(),(dx x g x f g f n x R x g x f ][)(),(∈ 证明：上述代数运算是内积；求出的一组标准正交基；3][x R （3）求与之间的距离；221x x ++2x 2x 1+−（4）证明：是的子空间；2][x R 3]x [R （5）写出2[][]3R x R x ∩的维数和一组基；二、 设22R ×是实数域R 上全体22×实矩阵构成的线性空间（按通常矩阵的加 法和数与矩阵的乘法）。

（1） 求22R ×的维数，并写出其一组基；（2） 在(1)所取基下的坐标； ⎥⎦⎤⎢⎣⎡−−3111（3） 设W 是实数域R 上全体22×实对称矩阵构成的线性空间（按通常矩阵的加法和数与矩阵的乘法）。

证明：W 是22R ×的子空间；并写出W 的维数和一组基；（4） 在W 中定义内积， )A B (tr )B ,A (T =W B ,A ∈求出W 的一组标准正交基；（5）求与之间的距离； ⎥⎦⎤⎢⎣⎡0331⎥⎦⎤⎢⎣⎡−1221 （6）设V 是实数域R 上全体22×实上三角矩阵构成的线性空间（按通常矩阵的加法和数与矩阵的乘法）。

证明：V 也是22R ×的子空间；并写出V 的维数和一组基；（7）写出子空间的一组基和维数。

可编辑修改精选全文完整版Solution Key to Some Exercises in Chapter 3 #5. Determine the kernel and range of each of the following linear transformations on 2P(a) (())'()p x xp x σ=(b) (())()'()p x p x p x σ=- (c) (())(0)(1)p x p x p σ=+Solution (a) Let ()p x ax b =+. (())p x ax σ=.(())0p x σ= if and only if 0ax = if and only if 0a =. Thus, ker(){|}b b R σ=∈The range of σis 2()P σ={|}ax a R ∈ (b) Let ()p x ax b =+. (())p x ax b a σ=+-.(())0p x σ= if and only if 0ax b a +-= if and only if 0a =and 0b =. Thus, ker(){0}σ=The range of σis 2()P σ=2{|,}P ax b a a b R +-∈=(c) Let ()p x ax b =+. (())p x bx a b σ=++.(())0p x σ= if and only if 0bx a b ++= if and only if 0a =and 0b =. Thus, ker(){0}σ=The range of σis 2()P σ=2{|,}P bx a b a b R ++∈= 备注: 映射的核以及映射的像都是集合,应该以集合的记号来表达或者用文字来叙述. #7. Let be the linear mapping that maps 2P into 2R defined by10()(())(0)p x dx p x p σ⎛⎫⎪= ⎪⎝⎭⎰ Find a matrix A such that()x A ασαββ⎛⎫+= ⎪⎝⎭.Solution1(1)1σ⎛⎫= ⎪⎝⎭ 1/2()0x σ⎛⎫= ⎪⎝⎭11/211/2()1010x ασαβαββ⎛⎫⎛⎫⎛⎫⎛⎫+=+= ⎪ ⎪⎪⎪⎝⎭⎝⎭⎝⎭⎝⎭Hence, 11/210A ⎛⎫= ⎪⎝⎭#10. Let σ be the transformation on 3P defined by(())'()"()p x xp x p x σ=+a) Find the matrix A representing σ with respect to 2[1,,]x x b) Find the matrix B representing σ with respect to 2[1,,1]x x + c) Find the matrix S such that 1B S AS -=d) If 2012()(1)p x a a x a x =+++, calculate (())n p x σ.Solution (a) (1)0σ= ()x x σ=22()22x x σ=+002010002A ⎛⎫⎪= ⎪ ⎪⎝⎭(b) (1)0σ=()x x σ=22(1)2(1)x x σ+=+000010002B ⎛⎫⎪= ⎪ ⎪⎝⎭(c)2[1,,1]x x +2[1,,]x x =101010001⎛⎫⎪⎪ ⎪⎝⎭The transition matrix from 2[1,,]x x to 2[1,,1]x x + is101010001S ⎛⎫ ⎪= ⎪ ⎪⎝⎭, 1B S AS -=(d) 2201212((1))2(1)n n a a x a x a x a x σ+++=++#11. Let A and B be n n ⨯ matrices. Show that if A is similar to B then there exist n n ⨯ matrices S and T , with S nonsingular, such thatA ST =andB TS =.Proof There exists a nonsingular matrix P such that 1A P BP -=. Let 1S P -=, T BP =. Then A ST =and B TS =.#12. Let σ be a linear transformation on the vector space V of dimension n . If there exist a vector v such that 1()v 0n σ-≠ and ()v 0n σ=, show that(a) 1,(),,()v v v n σσ- are linearly independent.(b) there exists a basis E for V such that the matrix representing σ with respect to the basis E is000010000010⎛⎫⎪⎪⎪⎪⎝⎭Proof(a) Suppose that1011()()v v v 0n n k k k σσ--+++= Then 11011(()())v v v 0n n n k k k σσσ---+++=That is, 12210110()()())()v v v v 0n n n n n k k k k σσσσ----+++==Thus, 0k must be zero since 1()v 0n σ-≠. 211111(()())()v v v 0n n n n k k k σσσσ----++==This will imply that 1k must be zero since 1()v 0n σ-≠.By repeating the process above, we obtain that 011,,,n k k k - must be all zero. Thisproves that1,(),,()v v v n σσ- are linearly independent.(b) Since 1,(),,()v v v n σσ- are n linearly independent, they form a basis for V .Denote 112,(),,()εv εv εv n n σσ-=== 12()εεσ= 23()εεσ= …….1()εεn n σ-= ()ε0n σ=12[(),(),,()]εεεn σσσ121[,,,,]εεεεn n -=000010000010⎛⎫⎪⎪⎪⎪⎝⎭#13. If A is a nonzero square matrix and k A O =for some positive integer k , show that A can not be similar to a diagonal matrix.Proof Suppose that A is similar to a diagonal matrix 12diag(,,,)n λλλ. Then for each i , there exists a nonzero vector x i such that x x i i i A λ= x x x 0k k i i i i i A λλ=== since k A O =.This will imply that 0i λ= for 1,2,,i n =. Thus, matrix A is similar to the zero matrix. Therefore, A O =since a matrix that is similar to the zero matrix must be the zero matrix, whichcontradicts the assumption.This contradiction shows that A can not be similar to a diagonal matrix. OrIf 112diag(,,,)n A P P λλλ-= then 112diag(,,,)k k k k n A P P λλλ-=. k A O = implies that 0i λ= for 1,2,,i n =. Hence, B O =. This will imply that A O =.Contradiction!。

南京航空航天大学07-14硕士研究生矩阵论试题2007 ~ 2008学年《矩阵论》 课程考试A 卷一、（20分）设矩阵⎪⎪⎪⎭⎫ ⎝⎛-----=111322211A ， （1）求A 的特征多项式和A 的全部特征值； （2）求A 的行列式因子、不变因子和初等因子；（3）求A 的最小多项式，并计算I A A 236-+；（4）写出A 的Jordan 标准形。

二、（20分）设22⨯R 是实数域R 上全体22⨯实矩阵构成的线性空间(按通常矩阵的加法和数与矩阵的乘法)。

（1）求22⨯R的维数，并写出其一组基；（2）设W 是全体22⨯实对称矩阵的集合， 证明：W 是22⨯R的子空间，并写出W 的维数和一组基；（3）在W 中定义内积W B A BA tr B A ∈=,),(),(其中，求出W 的一组标准正交基；（4）给出22⨯R 上的线性变换T ： 22,)(⨯∈∀+=R A A A A T T写出线性变换T 在（1）中所取基下的矩阵，并求T 的核)(T Ker 和值域)(T R 。

三、（20分）（1）设⎪⎪⎭⎫⎝⎛-=121312A ，求1A ，2A ，∞A ，F A ； （2）设nn ij C a A ⨯∈=)(，令ijji a n A ,*max ⋅=，证明：*是n n C ⨯上的矩阵范数并说明具有相容性；（3）证明：*2*1A A A n ≤≤。

四、（20分）已知矩阵⎪⎪⎪⎪⎪⎭⎫⎝⎛-=100100011111A ，向量⎪⎪⎪⎪⎪⎭⎫⎝⎛=2112b ， （1）求矩阵A 的QR 分解；（2）计算+A ；（3）用广义逆判断方程组b Ax =是否相容？若相容,求其通解;若不相容,求其极小最小二乘解。

五、（20分）（1）设矩阵⎪⎪⎪⎭⎫⎝⎛=⎪⎪⎪⎭⎫ ⎝⎛=15.025.011210,2223235t t B t t A ，其中t 为实数，问当t 满足什么条件时, B A >成立？（2）设n 阶Hermite 矩阵022121211>⎪⎪⎭⎫⎝⎛=A A A A A H，其中k k C A ⨯∈11，证明：0,012111122211>->-A A A A A H。

NUAALet 3P (the vector space of real polynomials of degree less than 3) defined by(())'()''()p x xp x p x σ=+.(1) Find the matrix A representing σ with respect to the ordered basis [21,,x x ] for 3P .(2) Find a basis for 3P such that with respect to this basis, the matrix B representing σ is diagonal.(3) Find the kernel （核） and range （值域）of this transformation. Solution: (1)221022x x x x σσσ===+（）（）（） 002010002A ⎛⎫⎪= ⎪ ⎪⎝⎭----------------------------------------------------------------------------------------------------------------- (2)101010001T ⎛⎫ ⎪= ⎪ ⎪⎝⎭(The column vectors of T are the eigenvectors of A)The corresponding eigenvectors in 3P are 1000010002T AT -⎛⎫⎪= ⎪ ⎪⎝⎭(T diagonalizes A ) 22[1,,1][1,,]x x x x T += . With respect to this new basis 2[1,,1]x x +, the representingmatrix of σis diagonal.------------------------------------------------------------------------------------------------------------------- (3) The kernel is the subspace consisting of all constant polynomials.The range is the subspace spanned by the vectors 2,1x x +-----------------------------------------------------------------------------------------------------------------------Let 020012A ⎛⎫⎪= ⎪ ⎪-⎝⎭.(1) Find all determinant divisors and elementary divisors of A .(2) Find a Jordan canonical form of A .(3) Compute At e . (Give the details of your computations.) Solution: (1)110020012I A λλλλ-⎛⎫ ⎪-=- ⎪ ⎪-⎝⎭,(特征多项式 2()(1)(2)p λλλ=--. Eigenvalues are 1, 2, 2.)Determinant divisor of order 1()1D λ=, 2()1D λ=, 23()()(1)(2)D p λλλλ==-- Elementary divisors are 2(1) and (2)λλ-- .---------------------------------------------------------------------------------------------------------------------- (2) The Jordan canonical form is100021002J ⎛⎫ ⎪= ⎪ ⎪⎝⎭--------------------------------------------------------------------------------------------------------------------------(3) For eigenvalue 1, 010010011I A ⎛⎫⎪-=- ⎪ ⎪-⎝⎭ ， An eigenvector is 1(1,0,0)T p = For eigenvalue 2, 1102000010I A ⎛⎫⎪-= ⎪ ⎪⎝⎭, An eigenvector is 2(0,0,1)T p =Solve 32(2)A I p p -=, 331100(2)00000101A I p p --⎛⎫⎛⎫⎪ ⎪-== ⎪ ⎪ ⎪ ⎪-⎝⎭⎝⎭we obtain that3(1,1,0)T p =-101001010P ⎛⎫ ⎪=- ⎪ ⎪⎝⎭, 1110001010P -⎛⎫⎪= ⎪ ⎪-⎝⎭ 1At J e Pe P -=22210100110001000101000010tt t t e e te e ⎛⎫⎛⎫⎛⎫⎪ ⎪ ⎪=- ⎪ ⎪ ⎪ ⎪ ⎪ ⎪-⎝⎭⎝⎭⎝⎭22220000t t t t t t e e e e tee ⎛⎫-⎪= ⎪ ⎪-⎝⎭ --------------------------------------------------------------------------------------------------------------------Suppose that ∈R A and O I A A =--65.(1) What are the possible minimal polynomials of A ? Explain.(2) In each case of part (1), what are the possible characteristic polynomials of A ? Explain.Solution:(1) An annihilating polynomial of A is 256x x --.The minimal polynomial of A divides any annihilating polynomial of A. The possible minimal polynomials are6x -, 1x +, and 256x x --.---------------------------------------------------------------------------------------------------------------(2) The minimal polynomial of A divides the characteristic polynomial of A. Since A is a matrix of order 3, the characteristic polynomial of A is of degree 3. The minimal polynomial of A and the characteristic polynomial of A have the same linear factors. Case 6x -, the characteristic polynomial is 3(6)x - Case 1x +, the characteristic polynomial is 3(1)x + Case 256x x --, the characteristic polynomial is 2(1)(6)x x +- or 2(6)(1)x x -+-------------------------------------------------------------------------------------------------------------------Let 120000A ⎛⎫=⎪⎝⎭. Find the Moore-Penrose inverse A +of A .Solution: ()12011200000A PG ⎛⎫⎛⎫=== ⎪ ⎪⎝⎭⎝⎭1()(1,0)T T P P P P +-==, 111()250T T G G GG +-⎛⎫⎪== ⎪ ⎪⎝⎭110112(1,0)2055000A G P +++⎛⎫⎛⎫ ⎪⎪=== ⎪ ⎪ ⎪ ⎪⎝⎭⎝⎭也可以用SVD 求.------------------------------------------------------------------------------------------------------------------Part II (选做题, 每题10分)请在以下题目中（第6至第9题）选择三题解答. 如果你做了四题，请在题号上画圈标明需要批改的三题. 否则，阅卷者会随意挑选三题批改，这可能影响你的成绩.Let 4P be the vector space consisting of all real polynomials of degree lessthan 4 with usual addition and scalar multiplication. Let 123,,x x x be three distinct real numbers. For each pair of polynomials f and g in 4P , define 31,()()i i i f g f x g x =<>=∑.Determine whether ,f g <> defines an inner product on 4P or not. Explain.Let n n A ⨯∈R . Show that if x x A =)(σis the orthogonal projection fromn R to )(A R , then A is symmetric and the eigenvalues ofA are all 1’s and 0’s.n n A ⨯∈C . Show that x x A H is real-valued for all n C x ∈if and only if Ais Hermitian.Let n n B A ⨯∈C ， be Hermitian matrices, and A bepositive definite. Show thatAB is similar to BA , and is similar to a real diagonal matrix.若正面不够书写，请写在反面.123()()()x x x x x x ---. Then ,0f f <>=. But 0f ≠. This does not define an inner product. For any x , ()()x x T A R A N A ⊥-∈=, ()x x 0T A A -=. Hence, T T A A A =. Thus. T A A =.From above, we have 2A A =. This will imply that λλ-2is an annihilating polynomial of A. The eigenvalue of A must be the roots of 02=-λλ. Thus, the eigenvalues of A are1’s and 0’s.See Thm 7.1.1, page 182. 也可以用其它方法.Since A is nonsingular, 1()AB A BA A -=. Hence, A is similar to BASince A is positive definite, there is a nonsingular hermitian matrix P such that H A PP =. 1()H H AB PP B P P BP P -==Since H P BP is Hermitian, it is similar to a real diagonal matrix.is similar to H AB P BP , H P BP is similar to a real diagonal matrix. Thus AB is similar to a real diagonal matrix.。

习题三1．证明下列问题：（1）若矩阵序列{}m A 收敛于A ，则{}Tm A 收敛于T A ，{}m A 收敛于A ；（2）若方阵级数∑∞=0m m m A c 收敛，则∑∑∞=∞==⎪⎭⎫ ⎝⎛00)(m mT m Tm m m A c A c .证明：（1）设矩阵,,2,1,)()( ==⨯m a A n n m ij m则,)()(n n m ji Tm a A ⨯=,)()(n n m ij m a A ⨯=,,2,1 =m设,)(n n ij a A ⨯=则n n ji T a A ⨯=)(，,)(n n ij a A ⨯=若矩阵序列{}m A 收敛于A ，即对任意的n j i ,,2,1, =，有ij m ij m a a =∞→)(lim ，则ji m ji m a a =∞→)(lim ，ij m ij m a a =∞→)(lim ，n j i ,,2,1, =，故{}T m A 收敛于TA ，{}m A 收敛于A .(2)设方阵级数∑∞=0m m mA c的部分和序列为,,,,21m S S S ，其中mm m A c A c c S +++= 10.若∑∞=0m m mA c收敛，设其和为S ，即S A cm m m=∑∞=0，或S S m m =∞→lim ，则T Tm m S S =∞→lim .而级数∑∞=0)(m mTmA c的部分和即为TmS ，故级数∑∞=0)(m m T m A c 收敛，且其和为T S ，即∑∑∞=∞==⎪⎭⎫ ⎝⎛00)(m m T m Tm m m A c A c .2.已知方阵序列{}m A 收敛于A ，且{}1-m A ，1-A 都存在，证明：（1）A A m m =∞→lim ；（2）{}11lim --∞→=A A m m .证明：设矩阵,,2,1,)()( ==⨯m a A n n m ij m ,)(n n ij a A ⨯=若矩阵序列{}m A 收敛于A ，即对任意的n j i ,,2,1, =，有ij m ij m a a =∞→)(lim .(1) 由于对任意的n j j j ,,,21 ，有,lim )(k kkj m kj m a a =∞→ n k ,,2,1 =， 故∑-∞→nn n j j j m nj m j m j j j j m a a a 2121)()(2)(1)()1(limτ＝∑-nn n j j j nj j j j j j a a a 21212121)()1(τ，而∑-=nn n j j j m nj m j m j j j j m a a a A 2121)()(2)(1)()1(τ，∑-=nn n j j j nj j j j j j a a a A 21212121)()1(τ,故A A m m =∞→lim .(2) 因为n n m ij m m A A A ⨯-=)(1)(1，n n ij A AA ⨯-=)(11. 其中)(m ij A ，ij A 分别为矩阵m A 与A 的代数余子式.与（1）类似可证明对任意的n j i ,,2,1, =，有ij m ij m A A =∞→)(lim ，结合A A m m =∞→lim ，有n n m ij m m A A ⨯∞→)(1lim)(＝n n ij A A⨯)(1， 即{}11lim --∞→=A A m m .3.设函数矩阵⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=321sin cos sin )(t t e t t t t t t A t ， 其中0≠t ，计算),(),(lim 0t A dt d t A t →),(22t A dtd ,)(t A dt d)(t A dt d . 解：根据函数矩阵的极限与导数的概念与计算方法，有（1）⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡=→→→→→→→→→→001011010lim 0lim 1lim lim lim sin limlim cos lim sin lim )(lim 300200000t t e ttt ttt A t t t t tt t t t t t ；（2）⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡--=⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡'''''''''=22323002sin cos 1sin cos )(01)()()sin ()(cos )(sin )(t t e t t t t t tt t e t t t t t t A dt dt t ； （3）⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡----==t e t t t t t t t A dtd dt d t A dt d t 6002cos 2sin )2(0cos sin ))(()(222；（4）=)(t A dt d '3201sin cos sin t t e tt t t tt)2cos 2(sin )sin cos 2(]1)cos (sin sin 3[32t t t t t t t t t t t t t e t +--+--++=（5）)(t A dt d ＝22302sin cos 1sin cos t t e t t t t t tt -- )sin cos (sin 3cos 32t t t t t e t t -+=.4．设函数矩阵⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=-00302)(222x e e x xe e x A x xx x ， 计算⎰10)(dx x A 和⎪⎭⎫ ⎝⎛⎰20)(x dt t A dx d . 解：根据函数矩阵积分变限积分函数的导数的概念与计算方法，有（1）⎰10)(dx x A ＝⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎣⎡⎰⎰⎰⎰⎰⎰-0030210102110210102xdx dx e dxe dx x dxxe dxe xx x x ⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎣⎡---=-0023011311)1(21212e e e ；（2）⎪⎭⎫ ⎝⎛⎰20)(x dt t A dx d ＝)(22x xA ＝⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡-00302224222222x e e x ex e x x x x. 5.设,))(,),(),((21Tn t y t y t y y =A 为n 阶常数对称矩阵，Ay y y f T =)(，证明：（1）dt dy A y dt df T 2=； （2）dtdy y y dt d T222=. 证明：（1）y A y Ay y Ay y dtdfT T T '+'='=)()(y A y Ay y T T T '+'=))((y A y T '=2dtdyA y T 2=，（2）dtdy y yy dt d y dt d TT 2)(22==. 6.证明关于迹的下列公式：（1）X X X tr dX d XX tr dX d T T 2)()(==； （2）T T T B B X tr dX d BX tr dX d ==)()(；（3）X A A AX X tr dXd T T )()(+=.其中m m ij m n ij n m ij a A b B x X ⨯⨯⨯===)(,)()(.证明：（1）因为∑∑====mi nj ij TTx X X tr XX tr 112)()(，而ij m i n j ij ij x x x 2)(112=∂∂∑∑==， 故X X X tr dXd XX tr dX d T T 2)()(== （2）因为n n mk kj ik x b BX ⨯=∑=)(1，则∑∑====n j mk kj jk TTx b B X tr BX tr 11)()(，而ji n j mk kj jk ij b x b x =∂∂∑∑==)(11， 故T T T B B X tr dXd BX tr dX d ==)()(. (3) 因为,212221212111⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡=mn n n m m Tx x x x x x x x x X⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=∑∑∑∑∑∑∑∑∑=========mk kn mk m k k mk mk k mk mk kn k mk k kmk k k mk kn k mk k k mk k k x a xax a x a x axa x a x a x a AX 112111212211211121111故)()()()(11ln 111111∑∑∑∑∑∑======++++=m l mk kn lk m l m k kj lk lj m l m k k lk l Tx a x x a x x a x AX X tr 则))(()(11∑∑==∂∂=∂∂m l mk kj lk lj ij Tij x a x x AX X tr x )]([111∑∑∑===∂∂+∂∂=mk kj lk ij lj mk kj lk ij ljml x a x x x a x x ∑∑==+=ml lj li mk kj ik x a x a 11故X A A X A AX AX X tr dXdT T T )()(+=+=. 7．证明：T T T T T T dXdb a dX da b b a dX d +=)(， 其中)(),(X b X a 为向量函数.证明：设Tm T m X b X b X b X b X a X a X a X a ))(,),(),(()(,))(,),(),(()(2121 ==，则∑==mi i i TX b X a X b X a 1)()()()(，故它是X 的数量函数，设)()()(X b X a X f T =，有),,,())()((21n TTx f x f x f X b X a dXd ∂∂∂∂∂∂= ⎪⎪⎭⎫ ⎝⎛⎪⎪⎭⎫ ⎝⎛∂∂+∂∂⎪⎪⎭⎫ ⎝⎛∂∂+∂∂=∑∑==m i n i i i n i m i i i i i x X b X a X b x X a x X b X a X b x X a 1111)()()()(,,)()()()( ∑∑∑===∂∂∂∂∂∂=mi i ni m i i i mi i i X b x X a X b x X a X b x X a 11211))()(,,)()(,)()(( ))()(,,)()(,)()((11211∑∑∑===∂∂∂∂∂∂+mi n i i m i i i mi i i x X b X a x X b X a x X b X aTT T TdXdb a dX da b +=. 8.在2R 中将向量Tx x ),(21表示成平面直角坐标系21,x x 中的点Tx x ),(21，分别画出下列不等式决定的向量Tx x x ),(21=全体所对应的几何图形：(1) ,11≤x (2) ，12≤x(3) 1≤∞x .解：根据,1211≤+=x x x ,122212≤+=x x x{}1,max 21≤=∞x x x ，作图如下：9.证明对任何nC y x ∈,，总有)(212222y x y x x y y x T T --+=+. 证明：因为y y x y y x x x y x y x yx T T T T T +++=++=+)()(22y y x y y x x x y x y x y x T T T T T +--=--=-)()(22故x y y x y x y x T T +=--+)(212222 10.证明：对任意的nC x ∈，有12x x x≤≤∞.证明：设Tn x x x x ),,,(21 =，则{}nn n x x x x x x x xx x x x +++=+++==∞21122221221,,,,,max由于{}22122221221)(),,,(max n nn x x x x x x x x x +++≤+++≤ ，故21222x xx≤≤∞，即12x x x≤≤∞.11.设n a a a ， ,,21是正实数，证明：对任意nT n C x x x X ∈=),,(21， ，2112⎪⎭⎫ ⎝⎛=∑=ni i i x a X是nC 中的向量范数.证明：因为（1）,02112≥⎪⎭⎫ ⎝⎛=∑=ni i i x a X 且00=⇔=X X ； （2）X k x a k x a k kx a kX ni i i ni i i ni i i =⎪⎭⎫⎝⎛=⎪⎭⎫ ⎝⎛=⎪⎭⎫ ⎝⎛=∑∑∑===2112211222112；（3）对于nT n C y y y Y ∈=),,(21， ，T n n y x y x y x Y X ),,(2211+++=+， ，则21212122)(2Y X Y X y a x a y x a YX ni ii ni ii ni ii i +=++≤+=+∑∑∑===故Y X Y X +≤+.因此2112⎪⎭⎫⎝⎛=∑=ni i i x a X 是nC 中的向量范数. 12.证明：ij nj i a n A ≤≤=,1m ax是矩阵n n ij a A ⨯=)(的范数，并且与向量的1－范数是相容的.证明:因为(1) 0m ax ,1≥=≤≤ij nj i a n A ,且O A =⇔0=A ;(2) A k a n k ka n kA ij nj i ij nj i =≥=≤≤≤≤,1,1m ax m ax ;(3) B A b n a n b a n B A ij nj i ij nj i ij ij nj i +=+≥+=+≤≤≤≤≤≤,1,1,1m ax m ax m ax(4)设Tn x x x X ),,,(21 =,则T nj j nj n j j j n j j j x a x a x a AX ),,,(11211∑∑∑==== ，故∑∑∑===+++=nj j njnj j jnj j jx ax ax aAX 11111∑∑∑=≤≤=≤≤=≤≤+++≤nj j nj nj nj j j nj nj jjnj x a x a xa 11121111max max max11,1max X A xa n nj jijnj i =≤∑=≤≤因此ij nj i a n A ≤≤=,1m ax 是与向量的1－范数相容的矩阵范数.13.设nn CA ⨯∈，且A 可逆，证明：11--≥AA .证明:由于I AA =-1,1=I ,则111--≤==A A AA I ,故11--≥AA .14.设nn CA ⨯∈，且,1<A 证明：A I -可逆，而且有（1）AA I -≤--11)(1；（2）AA I A I -≤---1)(1.证明:(1)由于A A I I A I 11)()(---+=-,故A A I I A A I I A I 111)()()(----+≤-+≤-,即 AA I -≤--11)(1.(2)因为A I A I =-+)(,两边右乘1)(-+A I ,可得11)()(--+=+-A I A A I I ,左乘A ,整理得11)()(--+-=+A I AA A A I A ,则111)()()(---++≤+-=+A I A A A A I AA A A I A ，即 AA I A I -≤---1)(1.15.设C l k CB A nn ∈∈⨯,,,证明：（1）Al k klkA ee e )(+=，特别地A A e e --=1)(;（2）当BA AB =时，BA AB BA ee e e e +==；（3）A e Ae e dtd At At At==；（4）当BA AB =时，B A B A B A sin cos cos sin )sin(±=±. 证明:(1)∑∑∑∞==-∞=+⎥⎦⎤⎢⎣⎡=+=000)()()(!1!)(n n m m n m m n n n n Al k lA kA C n n A l k e∑∑∑∑∞=∞=∞=∞=+++=+=-0000)()(!!)!()!(1)()()!(1m l l m m l lm m m l lA kA m l m l m l lA kA C m l l m nlA kA l l m m m l l m e e kA l kA m lA kA m l =⎪⎭⎫ ⎝⎛⎪⎭⎫ ⎝⎛==∑∑∑∑∞=∞=∞=∞=0000)(!1)(!1)()(!!1.又因为A A A A O e e e e I --+===)(,故A A e e --=1)(.(2)当BA AB =时,二项式公式∑===+nm mm n m n nB AC B A 0)(成立，故∑∑∑∞==-∞=+⎪⎭⎫ ⎝⎛=+=000!1)(!1n n m m m n m n n nBA B A C n B A n e∑∑∑∑∞=∞=∞=∞=+=+=-0000!!1)!(1m l m l m l ml m m l B A m l B A C m l l m nBA m m l l e eB m A l =⎪⎭⎫ ⎝⎛⎪⎭⎫ ⎝⎛=∑∑∞=∞=00!1!1同理，有A B l l m m BA e e A lB m e=⎪⎭⎫⎝⎛⎪⎭⎫ ⎝⎛=∑∑∞=∞=+00!1!1, 故B A A B B A e e e e e +==.(3)由于幂级数∑∞=0!1n nn t A n 对给定的矩阵A ,以及任意的t 都是绝对收敛的,且对任意的t 都是一致收敛的,因此科可对此幂级数逐项求导,则A l ll n n n n n n At Ae l t A A n t A t A n dt d e dt d ==-=⎪⎭⎫ ⎝⎛=∑∑∑∞=∞=-∞=0110!)!1(!1, 同理，有A e A l t A e dt d Al ll At =⎪⎪⎭⎫ ⎝⎛=∑∞=0! 故A e Ae e dtd At At At==. (4) 因为-+-++=432!41!31!21A iA A iA I e iA )!51!31()!41!21(5342 -+-+-+-=A A A i A A IA i A sin cos +=故)(21sin iA iAe e iA --=.又当BA AB =时，B A A B B A e e e e e +==,则()()iB iA iBiA B A i B A i e e e e i e e i B A --+-+-=-=+2121)sin()()( )]sin )(cos sin (cos )sin )(cos sin [(cos 21B i B A i A B i B A i A i---++= B A B A sin cos cos sin += 同理，可得B A B A B A sin cos cos sin )sin(-=-16.求下列三类矩阵的矩阵函数2,sin ,cos A e A A （1）当A 为幂等矩阵(A A =2)时；（2）当A 为对合矩阵(I A =2)时；（3）当A 为幂零矩阵(O A =2)时.解:(1) A A =2,设矩阵A 的秩为r ,则A 的特征值为1或0, A 可对角化为J O O O I AP P r =⎥⎦⎤⎢⎣⎡=-1,则11001sin 1sin sin sin --⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡==P P JP P AA PJP )1(sin )1(sin 1==-，11111cos 1cos cos cos --⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡==P P JP P A110011cos 11cos 1111--⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡--+⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=P P P PA I PJP I )11(cos )11(cos 1-+=-+=-111122--⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡==P e e P P Pe e J A1100111111--⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡--+⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=P e e P P PA e I PJP e I )1()1(1-+=-+=-(2) 当I A =2时，矩阵A 也可对角化,A 的特征值为1或1-, A 可对角化为J AP P =⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡--=-11111 ,其中1有m 个. 则111sin 1sin 1sin 1sin sin sin --⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡--==P P JP P AA PJP )1(sin )1(sin 1==-111cos 1cos 1cos 1cos cos cos --⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡==P P JP P A I )1(cos =eI P e e e e P P Pe e J A =⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡==--1122(3)当O A =2时, A 的特征值均为0,则存在可逆矩阵P ,使得11,--==PJP A J AP P ,其中⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=m J J J 1,又O A =2,则O P PJ A ==-122,于是O J J J m =⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=2212故Jordan 块k J 的阶数最多为2,不妨设0=k J ),,1(r k =,B J k =⎥⎦⎤⎢⎣⎡=0010),,1(m r k +=,即 ⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=B B J 0则1=k iJ e ,1=-k iJ e ),,1(r k =;⎥⎦⎤⎢⎣⎡=101i ekiJ ,⎥⎦⎤⎢⎣⎡-=-101i e k iJ ),,1(m r k +=. 故=--k k iJ iJ e e 0),,1(r k =,B ii e e k k iJ iJ 210020=⎥⎦⎤⎢⎣⎡=--),,1(m r k +=, 则2=+-k k iJ iJ e e ),,1(r k =,I e e k k iJ iJ 22002=⎥⎦⎤⎢⎣⎡=+-),,1(m r k +=, 因此J iB B i e e iJiJ 210021=⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=-- ,Ie e iJiJ 22222=⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=+- , 所以A PJP i i P e e P i e e i A iJ iJ iA iA =⋅=-=-=----11)2(21)(21)(21sin , I PIP P e e P e e A iJ iJ iA iA =⋅=+=+=----11221)(21)(21cos ,I I e e O A ==2.17.若矩阵A 的特征值的实部全为负，则O e At t =+∞→lim .证明: 设A 的特征值为0,1,<-=+=i i i i a j j b a λ,则存在可逆矩阵P ,使得11,--==PJP A J AP P ,其中⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=m J J J 1,i n i i i J ⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡=λλ11 则1121--⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎣⎡==P e e e P PPe et J tJ tJ Jt Atm, 其中⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎣⎡-=-t tt t t i n tttJ e tete e e n t tee ei i 11111111)!1(λλλλλλλ又)sin (cos lim lim lim t b j t b e e e i i t a t t jb t a t t t i i i i +==∞→+∞→∞→λ,且0<i a ,故0lim =∞→tt i eλ，因此O e t J t i =∞→lim ,则O e At t =+∞→lim .18．计算Ate 和At sin ，其中：（1）⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=110010002A ； （2）⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡-=010101010A ； （3）⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡---=6116100010A .解:(1)设,21=J ⎥⎦⎤⎢⎣⎡=11012J ,则⎥⎦⎤⎢⎣⎡=21J JA . 由于⎥⎦⎤⎢⎣⎡=t J tAt e e e 22,⎥⎦⎤⎢⎣⎡=t J t At 2sin 2sin sin , 且⎥⎦⎤⎢⎣⎡=t t ttJ e te e e02,⎥⎦⎤⎢⎣⎡=t t t tt J sin cos 0sin sin 2,则⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=t tt tAte te e e e 000002,⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=t t t t tAt sin cos 00sin 0002sin sin . (2)该矩阵的特征多项式为,11101)(3λλλλλϕ=---=最小多项式为3)(λλ=m .19.计算下列矩阵函数：（1）⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=221131122A ，求100A ； （2）⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡---=735946524A ，求Ae ；（3）⎥⎦⎤⎢⎣⎡-=4410A ，求4arcsin A； （4）⎥⎦⎤⎢⎣⎡=48816A ，求1)(-+A I 及21A 20．证明:I A A =+22cos sin ，A iI A e e =+π2，其中A 为任意方阵.证明:(1) 因为)(21sin iA iA e e i A --=,)(21cos iA iA e e A -+=, 故)2(41)(41sin 2222I e e e e A iA iA iA iA -+-=--=--,)2(41)(41cos 2222I e e e e A iA iA iA iA ++=+=--, 则I A A =+22cos sin .(2)因为矩阵iI π2的特征值均为i π2,故存在可逆矩阵P ,使得I P P P e e P e i i iI=⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=--1122211 πππ则A A iI A iI A e I e e e e ===+ππ2221.若A 为反实对称（反Hermite ）矩阵，则Ae 为实正交（酉）矩阵.证明: 因为∑∞==0!k k A k A e ,又∑∑===⎪⎪⎭⎫ ⎝⎛nk k n k k k A k A 0**0!)(!. 故**)(A A e e =.当A 为反实对称,即A A T-=时,I e e e e e e e O A A A A A T A T====-)(,故Ae 为实正交矩阵;当A 为反Hermite 矩阵,即A A -=*时,I e e e e e e e O A A A A A A ====-**)(,故Ae 为酉矩阵.22.若A 为Hermite 矩阵，则Aie 是酉矩阵，并说明当1=n 时此结论的意义.证明:因为A A =*,故Ai Ai Ai e e e -==*)(*)(,则I e e e e Ai Ai Ai Ai ==-*)(,故Aie 是酉矩阵.当A 为一阶Hermite 矩阵时, A 为一实数,设a A =,则上述命题为1=-ai ai e e23.将下列矩阵函数表示成矩阵幂级数，并说明对A 的限制： （1）shA ，（2）)ln(A I +，（3）A arctan 解：(1) ∑∞=++=012)!12(1n n A n shA , n n C A ⨯∈∀; (2) ∑∞=--=+111)1(4)ln(n nn A nA I ,1<A ; (3) ∑∞=++-=112121)1(arctan n n nA n A ,1<A . 24．设nn C A ⨯∈，证明：（1）)(A tr Ae e=，（2）AA ee ≤.证明:(1)设11,--==PJP A J AP P ,其中J 为若当标准形，则1121--⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎣⎡==P e e e P PPe e m J J J J A, 其中⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎣⎡=111111λλλe e e e iJ, 则mJ J J JJAe e e e Pe P e211===-trA J J J e e e e e n m ===++λλ 121.(2)设∑==Nk kN k A S 0!，则∑∑∑===≤≤=Nk kN k k Nk k NA k A k k A S 000!1!1!， 因为∑∞==!k kAk A e ，对上式两边取极限，得 Ak kAeA k e≤≤∑∞=0!1.25．设nn CA ⨯∈，且A 可逆，若λ是A 的任一特征值，则2211A A ≤≤-λ.证明:因为2)(A A =≤ρλ,故2A ≤λ.又对任意的nC X ∈,有2212122AX A AX A IXX--≤==,所以2212AX AX ≤-.设α是矩阵A 的特征值λ对应的特征向量,即λαα=A ,则222212αλλααα==≤-A A,故有λ≤-211A .因此2211A A ≤≤-λ.。

Solution Key (chapter 1)#2. TakeS , 2=. But 2S ∉. If 2S ∈, then there are rational numbers a and b , such that2=0a ≠ and 0b ≠.) This will lead to224232a b ab--=The right hand is a rational number and the left hand side is an irrational number. This is impossible. Thus, S is not closed under multiplication. Hence, S is not a field.#13. (a) Denote the set by S . Take 2()p x x x S =+∈, 2()q x x x S =-+∈.Then ()()2p x q x x S +=∉. S is not closed under addition. Hence, S is not a subspace. (Or: The set S does not contain the zero polynomial, hence, is not a subspace.) (b) Denote the set by S .Take 3()1p x x S =+∈, 3()1p x x S =-+∈. Then ()()2p x q x S +=∉. S is not closed under addition. Hence, S is not a subspace.(Or: The set S does not contain the zero polynomial, hence, is not a subspace.)(d) Denote the set by S . Take ()1p x x S =+∈, ()1p x x S =-+∈, ()()2p x q x S +=∉. S is not closed under addition. Hence, S is not a subspace.#15. (c) Denote the set by S . Take ()p x x S =∈. But ()p x x S -=-∉. Thus, the set S is not closed under scalar multiplication. Hence, S is not a subspace.(e) Denote the set by S . Take ()1p x x S =-∈ ()1q x x S =+∈. But ()()2p x q x x S +=∉. S is not closed under addition. Hence, S is not a subspace.#17. Since 12{,,,}u v v v i s span ∈ for each i , all combinations of 12,,,u u u r are also in 12{,,,}v v v s span . Thus, 12{,,,}u u u r span is a subspace of 12{,,,}v v v s span . Therefore, 12dim({,,,})u u u r span ≤ 12dim({,,,})v v v s span .#25. (a) Let 12(,,,)b b b n B = . Then 12(,,,)b b b n AB A A A = .If AB O =, then b 0i A = for 1,2,,i n = . ()b i N A ∈ for 1,2,,i n = . All lineawr combinations of 12,,,b b b n are also in ()N A . Thus, ()()R B N A ⊂. ()R B is a subspace of ()N A .If ()R B is a subspace of ()N A , then for each column b i of B , we must haveb 0i A =. Hence,12(,,,).b b b n AB A A A O ==(b) By part (a), we know that ()R B is a subspace of ()N A . Thus,()dim(())dim(())r B R B N A =≤. By the rank-nullity theorem, we obtain that()()d i m (())(r B r A N A r A n +≤+= #29. Let,A B S∈. Then ()T T T A B A B A B +=+=+, and ()T T kA kA kA ==. S is closedunder addition and scalar multiplication. Thus, S is a subspace ofn n R ⨯Let ,A B K ∈. Then ()()T T T A B A B A B A B +=+=--=-+, and ()()T T kA kA kA ==-. K is closed under addition and scalar multiplication. Thus, K is a subspace ofn n R ⨯The proof of n n R S K ⨯=⊕.Let .n n A R ⨯∈ Then 11()()22T T A A A A A =++-.1()2T A A + is symmetric and 1()2T A A - is anti-symmetric. This show that n n R S K ⨯=+. Next, we show that the sum S K + is a direct sum. If A S K ∈⋂, then we have both T A A = and T A A =-. This will imply that A A =-. Thus, A must be the zero matrix. This proves that the sum S K + is a direct sum.#32. Let ij E denote the matrix whose (,)i j entry is 1, zero elsewhere. For any()m n ij ij A a C ⨯=∈, where ,ij ij a b are real numbers, A can be written as1111n m n mij ij ij ij j i j i A a E b E =====∑∑.This shows that the matrices{|1,2,,,1,2,,} ij ij E i m j n == forms a spanningset form nC⨯. If1111n mn mijijij ij j i j i a Eb E O=====∑∑, then 0ij ij a = for1,2,,i m= ,1,2,,j n = . Thus, we must have 0ij ij a b ==for 1,2,,i m = , 1,2,,j n = . Therefore,{|1,2,,,1,2,,} ij ij E i m j n == forms a basis for m n C ⨯. The dimension is 2mn .。