前置知识: 线性代数

向量空间典型例题

20 minIntermediate2026/6/14

向量空间相关典型例题集锦,涵盖线性相关性判定、秩的计算、正交化、基与维数等题型。

1. 线性相关性

例1

α1,α2,α3\boldsymbol{\alpha}_1, \boldsymbol{\alpha}_2, \boldsymbol{\alpha}_3 线性无关,判断 kk 为何值时,α2α1\boldsymbol{\alpha}_2 - \boldsymbol{\alpha}_1kα3α2k\boldsymbol{\alpha}_3 - \boldsymbol{\alpha}_2α1α3\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_3 线性相关。

:设 x1(α2α1)+x2(kα3α2)+x3(α1α3)=0x_1(\boldsymbol{\alpha}_2 - \boldsymbol{\alpha}_1) + x_2(k\boldsymbol{\alpha}_3 - \boldsymbol{\alpha}_2) + x_3(\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_3) = 0

整理:(x1+x3)α1+(x1x2)α2+(kx2x3)α3=0(-x_1 + x_3)\boldsymbol{\alpha}_1 + (x_1 - x_2)\boldsymbol{\alpha}_2 + (kx_2 - x_3)\boldsymbol{\alpha}_3 = 0

α1,α2,α3\boldsymbol{\alpha}_1, \boldsymbol{\alpha}_2, \boldsymbol{\alpha}_3 线性无关:

{x1+x3=0x1x2=0kx2x3=0\begin{cases} -x_1 + x_3 = 0 \\ x_1 - x_2 = 0 \\ kx_2 - x_3 = 0 \end{cases}

系数行列式 1011100k1=1k\begin{vmatrix} -1 & 0 & 1 \\ 1 & -1 & 0 \\ 0 & k & -1 \end{vmatrix} = 1 - k

k=1k = 1 时,行列式为零,有非零解,线性相关。

例2

AAnn 阶方阵,α\boldsymbol{\alpha}nn 维非零列向量,α,Aα,A2α\boldsymbol{\alpha}, A\boldsymbol{\alpha}, A^2\boldsymbol{\alpha} 线性无关,A3α=3Aα2A2αA^3\boldsymbol{\alpha} = 3A\boldsymbol{\alpha} - 2A^2\boldsymbol{\alpha},求 A+I|A + I|

:由 A3α=3Aα2A2αA^3\boldsymbol{\alpha} = 3A\boldsymbol{\alpha} - 2A^2\boldsymbol{\alpha},即 (A3+2A23A)α=0(A^3 + 2A^2 - 3A)\boldsymbol{\alpha} = 0A(A2+2A3I)α=0A(A^2 + 2A - 3I)\boldsymbol{\alpha} = 0A(A+3I)(AI)α=0A(A + 3I)(A - I)\boldsymbol{\alpha} = 0

在基 α,Aα,A2α\boldsymbol{\alpha}, A\boldsymbol{\alpha}, A^2\boldsymbol{\alpha} 下,AA 的表示矩阵为:

B=(000103012)B = \begin{pmatrix} 0 & 0 & 0 \\ 1 & 0 & 3 \\ 0 & 1 & -2 \end{pmatrix}

A+I=B+I=100113011=13=4|A + I| = |B + I| = \begin{vmatrix} 1 & 0 & 0 \\ 1 & 1 & 3 \\ 0 & 1 & -1 \end{vmatrix} = -1 - 3 = -4

2. 向量组的秩

例3

α1=(1,2,1)T\boldsymbol{\alpha}_1 = (1, 2, -1)^Tα2=(2,4,λ)T\boldsymbol{\alpha}_2 = (2, 4, \lambda)^Tα3=(1,λ,1)T\boldsymbol{\alpha}_3 = (1, \lambda, 1)^T,求 α1,α2,α3\boldsymbol{\alpha}_1, \boldsymbol{\alpha}_2, \boldsymbol{\alpha}_3 的秩。

A=(12124λ1λ1)A = \begin{pmatrix} 1 & 2 & 1 \\ 2 & 4 & \lambda \\ -1 & \lambda & 1 \end{pmatrix}

r22r1,r3+r1(12100λ20λ+22)\xrightarrow{r_2-2r_1, r_3+r_1} \begin{pmatrix} 1 & 2 & 1 \\ 0 & 0 & \lambda-2 \\ 0 & \lambda+2 & 2 \end{pmatrix}

λ2\lambda \neq 2λ2\lambda \neq -2r(A)=3r(A) = 3

λ=2\lambda = 2(121000042)\begin{pmatrix} 1 & 2 & 1 \\ 0 & 0 & 0 \\ 0 & 4 & 2 \end{pmatrix}r(A)=2r(A) = 2

λ=2\lambda = -2(121004002)\begin{pmatrix} 1 & 2 & 1 \\ 0 & 0 & -4 \\ 0 & 0 & 2 \end{pmatrix}r(A)=2r(A) = 2

例4

r(A)=rr(A) = rAα1=Aα2=Aα3=bA\boldsymbol{\alpha}_1 = A\boldsymbol{\alpha}_2 = A\boldsymbol{\alpha}_3 = \boldsymbol{b}α1,α2,α3\boldsymbol{\alpha}_1, \boldsymbol{\alpha}_2, \boldsymbol{\alpha}_3 互不相同),求 r(α1α2,α1α3)r(\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_2, \boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_3)

A(α1α2)=0A(\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_2) = 0A(α1α3)=0A(\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_3) = 0

α1α2\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_2α1α3\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_3 都是 Ax=0Ax = 0 的解,且 α1α20\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_2 \neq 0

α1α2\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_2α1α3\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_3 线性相关,则 α1α3=k(α1α2)\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_3 = k(\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_2),即 (1k)α1+kα2α3=0(1-k)\boldsymbol{\alpha}_1 + k\boldsymbol{\alpha}_2 - \boldsymbol{\alpha}_3 = 0。这取决于具体条件。

一般地,r(α1α2,α1α3)2r(\boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_2, \boldsymbol{\alpha}_1 - \boldsymbol{\alpha}_3) \leq 2,且至少为 11

3. 正交化

例5

α1=(1,1,1)T\boldsymbol{\alpha}_1 = (1, 1, 1)^Tα2=(1,0,1)T\boldsymbol{\alpha}_2 = (1, 0, 1)^Tα3=(0,1,1)T\boldsymbol{\alpha}_3 = (0, 1, 1)^T 进行施密特正交化。

β1=α1=(1,1,1)T\boldsymbol{\beta}_1 = \boldsymbol{\alpha}_1 = (1, 1, 1)^T

β2=α2(α2,β1)(β1,β1)β1=(1,0,1)T23(1,1,1)T=(13,23,13)T\boldsymbol{\beta}_2 = \boldsymbol{\alpha}_2 - \frac{(\boldsymbol{\alpha}_2, \boldsymbol{\beta}_1)}{(\boldsymbol{\beta}_1, \boldsymbol{\beta}_1)}\boldsymbol{\beta}_1 = (1, 0, 1)^T - \frac{2}{3}(1, 1, 1)^T = \left(\frac{1}{3}, -\frac{2}{3}, \frac{1}{3}\right)^T

β3=α3(α3,β1)(β1,β1)β1(α3,β2)(β2,β2)β2\boldsymbol{\beta}_3 = \boldsymbol{\alpha}_3 - \frac{(\boldsymbol{\alpha}_3, \boldsymbol{\beta}_1)}{(\boldsymbol{\beta}_1, \boldsymbol{\beta}_1)}\boldsymbol{\beta}_1 - \frac{(\boldsymbol{\alpha}_3, \boldsymbol{\beta}_2)}{(\boldsymbol{\beta}_2, \boldsymbol{\beta}_2)}\boldsymbol{\beta}_2

(α3,β1)=2(\boldsymbol{\alpha}_3, \boldsymbol{\beta}_1) = 2(α3,β2)=23+13=13(\boldsymbol{\alpha}_3, \boldsymbol{\beta}_2) = -\frac{2}{3} + \frac{1}{3} = -\frac{1}{3}

(β2,β2)=19+49+19=23(\boldsymbol{\beta}_2, \boldsymbol{\beta}_2) = \frac{1}{9} + \frac{4}{9} + \frac{1}{9} = \frac{2}{3}

β3=(0,1,1)T23(1,1,1)T1/32/3(13,23,13)T\boldsymbol{\beta}_3 = (0, 1, 1)^T - \frac{2}{3}(1, 1, 1)^T - \frac{-1/3}{2/3}\left(\frac{1}{3}, -\frac{2}{3}, \frac{1}{3}\right)^T

=(0,1,1)T(23,23,23)T+(16,13,16)T=(12,0,12)T= (0, 1, 1)^T - \left(\frac{2}{3}, \frac{2}{3}, \frac{2}{3}\right)^T + \left(\frac{1}{6}, -\frac{1}{3}, \frac{1}{6}\right)^T = \left(-\frac{1}{2}, 0, \frac{1}{2}\right)^T

单位化:

e1=13(1,1,1)T\boldsymbol{e}_1 = \frac{1}{\sqrt{3}}(1, 1, 1)^Te2=16(1,2,1)T\boldsymbol{e}_2 = \frac{1}{\sqrt{6}}(1, -2, 1)^Te3=12(1,0,1)T\boldsymbol{e}_3 = \frac{1}{\sqrt{2}}(-1, 0, 1)^T

4. 基与维数

例6

求矩阵 A=(123424681111)A = \begin{pmatrix} 1 & 2 & 3 & 4 \\ 2 & 4 & 6 & 8 \\ 1 & 1 & 1 & 1 \end{pmatrix} 的零空间 N(A)N(A) 的基和维数。

A(123400000123)(101201230000)A \to \begin{pmatrix} 1 & 2 & 3 & 4 \\ 0 & 0 & 0 & 0 \\ 0 & -1 & -2 & -3 \end{pmatrix} \to \begin{pmatrix} 1 & 0 & -1 & -2 \\ 0 & 1 & 2 & 3 \\ 0 & 0 & 0 & 0 \end{pmatrix}

r(A)=2r(A) = 2dim(N(A))=42=2\dim(N(A)) = 4 - 2 = 2

同解方程组:{x1=x3+2x4x2=2x33x4\begin{cases} x_1 = x_3 + 2x_4 \\ x_2 = -2x_3 - 3x_4 \end{cases}

基础解系:ξ1=(1,2,1,0)T\boldsymbol{\xi}_1 = (1, -2, 1, 0)^Tξ2=(2,3,0,1)T\boldsymbol{\xi}_2 = (2, -3, 0, 1)^T

例7

V={(x1,x2,x3)Tx1+x2+x3=0}V = \{(x_1, x_2, x_3)^T \mid x_1 + x_2 + x_3 = 0\},求 VV 的基和维数。

VVAx=0Ax = 0 的解空间,其中 A=(1,1,1)A = (1, 1, 1)

r(A)=1r(A) = 1dim(V)=31=2\dim(V) = 3 - 1 = 2

基础解系:ξ1=(1,1,0)T\boldsymbol{\xi}_1 = (-1, 1, 0)^Tξ2=(1,0,1)T\boldsymbol{\xi}_2 = (-1, 0, 1)^T

例8

证明 Rn\mathbb{R}^n 中任意 nn 个线性无关的向量构成 Rn\mathbb{R}^n 的一组基。

证明:设 α1,,αn\boldsymbol{\alpha}_1, \ldots, \boldsymbol{\alpha}_n 线性无关,对任意 βRn\boldsymbol{\beta} \in \mathbb{R}^nα1,,αn,β\boldsymbol{\alpha}_1, \ldots, \boldsymbol{\alpha}_n, \boldsymbol{\beta}n+1n+1nn 维向量,必线性相关。

故存在不全为零的 k1,,kn,kn+1k_1, \ldots, k_n, k_{n+1} 使得 k1α1++knαn+kn+1β=0k_1\boldsymbol{\alpha}_1 + \cdots + k_n\boldsymbol{\alpha}_n + k_{n+1}\boldsymbol{\beta} = 0

kn+1=0k_{n+1} = 0,则 k1α1++knαn=0k_1\boldsymbol{\alpha}_1 + \cdots + k_n\boldsymbol{\alpha}_n = 0,由线性无关得 k1==kn=0k_1 = \cdots = k_n = 0,矛盾。

kn+10k_{n+1} \neq 0β\boldsymbol{\beta} 可由 α1,,αn\boldsymbol{\alpha}_1, \ldots, \boldsymbol{\alpha}_n 线性表示。

5. 正交矩阵

例9

AAnn 阶正交矩阵,A=1|A| = 1nn 为奇数,证明 AI=0|A - I| = 0

证明

AI=AAAT=A(IAT)=AIAT=IAT|A - I| = |A - AA^T| = |A(I - A^T)| = |A| \cdot |I - A^T| = |I - A^T|

=(IA)T=IA=(AI)=(1)nAI=AI= |(I - A)^T| = |I - A| = |-(A - I)| = (-1)^n|A - I| = -|A - I|

nn 为奇数时 (1)n=1(-1)^n = -1

2AI=02|A - I| = 0AI=0|A - I| = 0

例10

AA 为三阶正交矩阵,A=1|A| = 1α=(1,0,0)T\boldsymbol{\alpha} = (1, 0, 0)^TAα=(0,1,0)TA\boldsymbol{\alpha} = (0, 1, 0)^T,求 AA

AA 的第一列为 (0,1,0)T(0, 1, 0)^T

A=(0ad1be0cf)A = \begin{pmatrix} 0 & a & d \\ 1 & b & e \\ 0 & c & f \end{pmatrix}

ATA=IA^TA = I:第一列与第二列正交:b=0b = 0;第二列与第三列正交:ad+be+cf=ad+cf=0ad + be + cf = ad + cf = 0;第二列单位:a2+c2=1a^2 + c^2 = 1;第三列单位:d2+e2+f2=1d^2 + e^2 + f^2 = 1

A=1|A| = 1A=af+cd=1|A| = -a f + c d = 1(展开第一列)

第一行单位:a2+d2=1a^2 + d^2 = 1,第三行单位:c2+f2=1c^2 + f^2 = 1

结合 a2+c2=1a^2 + c^2 = 1a2+d2=1a^2 + d^2 = 1,得 c2=d2c^2 = d^2

a=cosθa = \cos\thetac=sinθc = \sin\theta,则 d=±sinθd = \pm\sin\thetaf=cosθf = \mp\cos\theta

af+cd=cosθcosθ+sinθsinθ=1-af + cd = \cos\theta \cdot \cos\theta + \sin\theta \cdot \sin\theta = 1(取 d=sinθ,f=cosθd = -\sin\theta, f = \cos\theta 时)

cosθ(cosθ)+sinθsinθ=cos2θ+sin2θ=1-\cos\theta \cdot (-\cos\theta) + \sin\theta \cdot \sin\theta = \cos^2\theta + \sin^2\theta = 1(取 d=sinθ,f=cosθd = \sin\theta, f = -\cos\theta 时)

还需满足 ad+cf=0ad + cf = 0cosθd+sinθf=0\cos\theta \cdot d + \sin\theta \cdot f = 0

d=sinθ,f=cosθd = -\sin\theta, f = \cos\thetacosθsinθ+sinθcosθ=0-\cos\theta\sin\theta + \sin\theta\cos\theta = 0

ee 由第三列单位确定:sin2θ+e2+cos2θ=1\sin^2\theta + e^2 + \cos^2\theta = 1e=0e = 0

A=(0cosθsinθ1000sinθcosθ)A = \begin{pmatrix} 0 & \cos\theta & -\sin\theta \\ 1 & 0 & 0 \\ 0 & \sin\theta & \cos\theta \end{pmatrix}

其中 θ\theta 为任意角度。