卷 1 填空题 本题共5分,每小题3分,满分15分
1 lim x → 0 3 sin x + x 2 cos 1 x ( 1 + cos x ) ln ( 1 + x ) =
\lim_{x \to 0} \frac{3\sin x + x^2\cos \frac{1}{x}}{(1 + \cos x)\ln(1 + x)} =
x → 0 lim ( 1 + cos x ) ln ( 1 + x ) 3 sin x + x 2 cos x 1 = 【答案】
3 2 \frac{3}{2} 2 3
【解析】
考虑极限
lim x → 0 3 sin x + x 2 cos 1 x ( 1 + cos x ) ln ( 1 + x ) \lim_{x \to 0} \frac{3\sin x + x^2\cos \frac{1}{x}}{(1 + \cos x)\ln(1 + x)} lim x → 0 ( 1 + c o s x ) l n ( 1 + x ) 3 s i n x + x 2 c o s x 1
。 当
x → 0 x \to 0 x → 0
时,分子中的
3 sin x ∼ 3 x 3\sin x \sim 3x 3 sin x ∼ 3 x
,而
x 2 cos 1 x x^2\cos \frac{1}{x} x 2 cos x 1
由于
∣ cos 1 x ∣ ≤ 1 |\cos \frac{1}{x}| \leq 1 ∣ cos x 1 ∣ ≤ 1
且
x 2 → 0 x^2 \to 0 x 2 → 0
,因此
x 2 cos 1 x → 0 x^2\cos \frac{1}{x} \to 0 x 2 cos x 1 → 0
,故分子等价于
3 x 3x 3 x
。 分母中,
1 + cos x → 2 1 + \cos x \to 2 1 + cos x → 2
,
ln ( 1 + x ) ∼ x \ln(1 + x) \sim x ln ( 1 + x ) ∼ x
,因此分母等价于
2 x 2x 2 x
。 于是,原极限化为
lim x → 0 3 x 2 x = 3 2 \lim_{x \to 0} \frac{3x}{2x} = \frac{3}{2} lim x → 0 2 x 3 x = 2 3
。 Alternatively, 使用夹逼定理:由于
∣ cos 1 x ∣ ≤ 1 |\cos \frac{1}{x}| \leq 1 ∣ cos x 1 ∣ ≤ 1
,有
3 sin x − x 2 ( 1 + cos x ) ln ( 1 + x ) ≤ 3 sin x + x 2 cos 1 x ( 1 + cos x ) ln ( 1 + x ) ≤ 3 sin x + x 2 ( 1 + cos x ) ln ( 1 + x ) \frac{3\sin x - x^2}{(1 + \cos x)\ln(1 + x)} \leq \frac{3\sin x + x^2\cos \frac{1}{x}}{(1 + \cos x)\ln(1 + x)} \leq \frac{3\sin x + x^2}{(1 + \cos x)\ln(1 + x)} ( 1 + cos x ) ln ( 1 + x ) 3 sin x − x 2 ≤ ( 1 + cos x ) ln ( 1 + x ) 3 sin x + x 2 cos x 1 ≤ ( 1 + cos x ) ln ( 1 + x ) 3 sin x + x 2 当
x → 0 x \to 0 x → 0
时,左右两边的极限均为
3 2 \frac{3}{2} 2 3
,故由夹逼定理,原极限为
3 2 \frac{3}{2} 2 3
。
2 设幂级数
∑ n = 0 ∞ a n x n \sum_{n = 0}^{\infty}a_n x^n ∑ n = 0 ∞ a n x n
的收敛半径为
3 3 3
,
则幂级数
∑ n = 1 ∞ n a n ( x − 1 ) n + 1 \sum_{n = 1}^{\infty}na_n (x - 1)^{n + 1} ∑ n = 1 ∞ n a n ( x − 1 ) n + 1
的收敛区间为 ______.
【答案】
( − 2 , 4 ) (-2,4) ( − 2 , 4 )
【解析】 已知幂级数
∑ n = 0 ∞ a n x n \sum_{n=0}^{\infty} a_n x^n ∑ n = 0 ∞ a n x n
的收敛半径为 3,因此其收敛区间为
( − 3 , 3 ) (-3,3) ( − 3 , 3 )
(端点收敛性未知)。
考虑幂级数
∑ n = 1 ∞ n a n ( x − 1 ) n + 1 .
\sum_{n=1}^{\infty} n a_n (x-1)^{n+1}.
n = 1 ∑ ∞ n a n ( x − 1 ) n + 1 . 令
y = x − 1 y = x-1 y = x − 1
,则原级数化为
∑ n = 1 ∞ n a n y n + 1 = y ∑ n = 1 ∞ n a n y n .
\sum_{n=1}^{\infty} n a_n y^{n+1} = y \sum_{n=1}^{\infty} n a_n y^n.
n = 1 ∑ ∞ n a n y n + 1 = y n = 1 ∑ ∞ n a n y n . 由于
∑ n = 0 ∞ a n x n \sum_{n=0}^{\infty} a_n x^n ∑ n = 0 ∞ a n x n
的收敛半径为 3,有
lim sup n → ∞ ∣ a n ∣ 1 / n = 1 3 .
\limsup_{n \to \infty} |a_n|^{1/n} = \frac{1}{3}.
n → ∞ lim sup ∣ a n ∣ 1/ n = 3 1 . 对于级数
∑ n = 1 ∞ n a n y n \sum_{n=1}^{\infty} n a_n y^n ∑ n = 1 ∞ n a n y n
,
lim sup n → ∞ ∣ n a n ∣ 1 / n = lim sup n → ∞ n 1 / n ⋅ ∣ a n ∣ 1 / n = 1 ⋅ 1 3 = 1 3 ,
\limsup_{n \to \infty} |n a_n|^{1/n} = \limsup_{n \to \infty} n^{1/n} \cdot |a_n|^{1/n} = 1 \cdot \frac{1}{3} = \frac{1}{3},
n → ∞ lim sup ∣ n a n ∣ 1/ n = n → ∞ lim sup n 1/ n ⋅ ∣ a n ∣ 1/ n = 1 ⋅ 3 1 = 3 1 , 因此其收敛半径也为 3。
于是
∑ n = 1 ∞ n a n y n \sum_{n=1}^{\infty} n a_n y^n ∑ n = 1 ∞ n a n y n
在
∣ y ∣ < 3 |y| < 3 ∣ y ∣ < 3
时收敛,在
∣ y ∣ > 3 |y| > 3 ∣ y ∣ > 3
时发散。从而
∑ n = 1 ∞ n a n y n + 1
\sum_{n=1}^{\infty} n a_n y^{n+1}
n = 1 ∑ ∞ n a n y n + 1 在
∣ y ∣ < 3 |y| < 3 ∣ y ∣ < 3
时收敛,在
∣ y ∣ > 3 |y| > 3 ∣ y ∣ > 3
时发散。
代回
y = x − 1 y = x-1 y = x − 1
,即当
∣ x − 1 ∣ < 3 |x-1| < 3 ∣ x − 1∣ < 3
时级数收敛,解得
− 2 < x < 4 -2 < x < 4 − 2 < x < 4
。
当
∣ x − 1 ∣ = 3 |x-1| = 3 ∣ x − 1∣ = 3
时,即
x = − 2 x = -2 x = − 2
或
x = 4 x = 4 x = 4
,级数变为
∑ n = 1 ∞ n a n ( ± 3 ) n + 1 .
\sum_{n=1}^{\infty} n a_n (\pm 3)^{n+1}.
n = 1 ∑ ∞ n a n ( ± 3 ) n + 1 . 由于原级数在
x = ± 3 x = \pm 3 x = ± 3
处的收敛性未知,且
∑ n a n ( ± 3 ) n \sum n a_n (\pm 3)^n ∑ n a n ( ± 3 ) n
可能发散,因此端点
x = − 2 x = -2 x = − 2
和
x = 4 x = 4 x = 4
处的收敛性无法确定,故收敛区间为开区间
( − 2 , 4 ) (-2,4) ( − 2 , 4 )
。
综上,幂级数
∑ n = 1 ∞ n a n ( x − 1 ) n + 1
\sum_{n=1}^{\infty} n a_n (x-1)^{n+1}
n = 1 ∑ ∞ n a n ( x − 1 ) n + 1 的收敛区间为
( − 2 , 4 ) (-2,4) ( − 2 , 4 )
。
3 对数螺线
ρ = e θ \rho = \e^{\theta} ρ = e θ
在点
( ρ , θ ) = ( e π 2 , π 2 ) (\rho ,\theta) = \left(\e^{\frac{\pi}{2}},\tfrac{\pi}{2} \right) ( ρ , θ ) = ( e 2 π , 2 π )
处的切线的直角坐标方程为 ______.
【答案】
x + y = e π 2 x + y = e^{\frac{\pi}{2}} x + y = e 2 π 【解析】 给定对数螺线
ρ = e θ \rho = e^{\theta} ρ = e θ
在点
( ρ , θ ) = ( e π 2 , π 2 ) (\rho, \theta) = \left(e^{\frac{\pi}{2}}, \frac{\pi}{2}\right) ( ρ , θ ) = ( e 2 π , 2 π )
处,首先将该点转换为直角坐标:
x = ρ cos θ = e π 2 cos π 2 = 0 x = \rho \cos \theta = e^{\frac{\pi}{2}} \cos \frac{\pi}{2} = 0 x = ρ cos θ = e 2 π cos 2 π = 0
y = ρ sin θ = e π 2 sin π 2 = e π 2 y = \rho \sin \theta = e^{\frac{\pi}{2}} \sin \frac{\pi}{2} = e^{\frac{\pi}{2}} y = ρ sin θ = e 2 π sin 2 π = e 2 π 因此点为
( 0 , e π 2 ) (0, e^{\frac{\pi}{2}}) ( 0 , e 2 π )
。
求切线斜率,由极坐标关系
x = e θ cos θ x = e^{\theta} \cos \theta x = e θ cos θ
和
y = e θ sin θ y = e^{\theta} \sin \theta y = e θ sin θ
,对参数
θ \theta θ
求导:
d x d θ = e θ ( cos θ − sin θ ) \frac{dx}{d\theta} = e^{\theta} (\cos \theta - \sin \theta) d θ d x = e θ ( cos θ − sin θ )
d y d θ = e θ ( sin θ + cos θ ) \frac{dy}{d\theta} = e^{\theta} (\sin \theta + \cos \theta) d θ d y = e θ ( sin θ + cos θ ) 则
d y d x = d y / d θ d x / d θ = sin θ + cos θ cos θ − sin θ \frac{dy}{dx} = \frac{dy/d\theta}{dx/d\theta} = \frac{\sin \theta + \cos \theta}{\cos \theta - \sin \theta} d x d y = d x / d θ d y / d θ = cos θ − sin θ sin θ + cos θ 在
θ = π 2 \theta = \frac{\pi}{2} θ = 2 π
处:
d y d x = sin π 2 + cos π 2 cos π 2 − sin π 2 = 1 + 0 0 − 1 = − 1 \frac{dy}{dx} = \frac{\sin \frac{\pi}{2} + \cos \frac{\pi}{2}}{\cos \frac{\pi}{2} - \sin \frac{\pi}{2}} = \frac{1 + 0}{0 - 1} = -1 d x d y = cos 2 π − sin 2 π sin 2 π + cos 2 π = 0 − 1 1 + 0 = − 1 切线斜率为
− 1 -1 − 1
。
使用点斜式方程:
y − e π 2 = − 1 ⋅ ( x − 0 ) y - e^{\frac{\pi}{2}} = -1 \cdot (x - 0) y − e 2 π = − 1 ⋅ ( x − 0 ) 即
x + y = e π 2 x + y = e^{\frac{\pi}{2}} x + y = e 2 π 故切线的直角坐标方程为
x + y = e π 2 x + y = e^{\frac{\pi}{2}} x + y = e 2 π
。
4 设
A = ( 1 2 − 2 4 t 3 3 − 1 1 ) A = \begin{pmatrix}
1 & 2 & -2 \\
4 & t & 3 \\
3 & -1 & 1
\end{pmatrix} A = 1 4 3 2 t − 1 − 2 3 1
,
B B B
为三阶非零矩阵,且
A B = O AB = O A B = O
,则
t = t = t =
______.
【答案】
− 3 -3 − 3
【解析】 由于
A B = O AB = O A B = O
且
B B B
为非零矩阵,则
A A A
不可逆,故
det ( A ) = 0 \det(A) = 0 det ( A ) = 0
。 计算行列式:
det ( A ) = det ( 1 2 − 2 4 t 3 3 − 1 1 ) = 1 ⋅ det ( t 3 − 1 1 ) − 2 ⋅ det ( 4 3 3 1 ) + ( − 2 ) ⋅ det ( 4 t 3 − 1 ) \det(A) = \det \begin{pmatrix}
1 & 2 & -2 \\
4 & t & 3 \\
3 & -1 & 1
\end{pmatrix} = 1 \cdot \det \begin{pmatrix} t & 3 \\ -1 & 1 \end{pmatrix} - 2 \cdot \det \begin{pmatrix} 4 & 3 \\ 3 & 1 \end{pmatrix} + (-2) \cdot \det \begin{pmatrix} 4 & t \\ 3 & -1 \end{pmatrix} det ( A ) = det 1 4 3 2 t − 1 − 2 3 1 = 1 ⋅ det ( t − 1 3 1 ) − 2 ⋅ det ( 4 3 3 1 ) + ( − 2 ) ⋅ det ( 4 3 t − 1 ) 其中:
det ( t 3 − 1 1 ) = t ⋅ 1 − 3 ⋅ ( − 1 ) = t + 3 \det \begin{pmatrix} t & 3 \\ -1 & 1 \end{pmatrix} = t \cdot 1 - 3 \cdot (-1) = t + 3 det ( t − 1 3 1 ) = t ⋅ 1 − 3 ⋅ ( − 1 ) = t + 3
det ( 4 3 3 1 ) = 4 ⋅ 1 − 3 ⋅ 3 = 4 − 9 = − 5 \det \begin{pmatrix} 4 & 3 \\ 3 & 1 \end{pmatrix} = 4 \cdot 1 - 3 \cdot 3 = 4 - 9 = -5 det ( 4 3 3 1 ) = 4 ⋅ 1 − 3 ⋅ 3 = 4 − 9 = − 5
det ( 4 t 3 − 1 ) = 4 ⋅ ( − 1 ) − t ⋅ 3 = − 4 − 3 t \det \begin{pmatrix} 4 & t \\ 3 & -1 \end{pmatrix} = 4 \cdot (-1) - t \cdot 3 = -4 - 3t det ( 4 3 t − 1 ) = 4 ⋅ ( − 1 ) − t ⋅ 3 = − 4 − 3 t 代入得:
det ( A ) = ( t + 3 ) − 2 ⋅ ( − 5 ) + ( − 2 ) ⋅ ( − 4 − 3 t ) = t + 3 + 10 + 8 + 6 t = 7 t + 21 \det(A) = (t + 3) - 2 \cdot (-5) + (-2) \cdot (-4 - 3t) = t + 3 + 10 + 8 + 6t = 7t + 21 det ( A ) = ( t + 3 ) − 2 ⋅ ( − 5 ) + ( − 2 ) ⋅ ( − 4 − 3 t ) = t + 3 + 10 + 8 + 6 t = 7 t + 21 设
det ( A ) = 0 \det(A) = 0 det ( A ) = 0
,有
7 t + 21 = 0 7t + 21 = 0 7 t + 21 = 0
,解得
t = − 3 t = -3 t = − 3
。 当
t = − 3 t = -3 t = − 3
时,
A A A
奇异,存在非零矩阵
B B B
满足
A B = O AB = O A B = O
。
5 袋中有
50 50 50
个乒乓球,其中
20 20 20
个是黄球,
30 30 30
个是白球.
今有两人依次随机地从袋中各取一球,取后不放回,则第二个人取得黄球的概率是 ______.
【答案】
【解析】
设第二个人取到黄球为事件
B B B
。 根据全概率公式:
P ( B ) = P ( B ∣ A 1 ) ⋅ P ( A 1 ) + P ( B ∣ A 2 ) ⋅ P ( A 2 )
P(B) = P(B \mid A_1) \cdot P(A_1) + P(B \mid A_2) \cdot P(A_2)
P ( B ) = P ( B ∣ A 1 ) ⋅ P ( A 1 ) + P ( B ∣ A 2 ) ⋅ P ( A 2 ) 其中:
A 1 A_1 A 1
:第一个人取到黄球A 2 A_2 A 2
:第一个人取到白球已知:
P ( A 1 ) = 20 50 = 2 5 , P ( A 2 ) = 30 50 = 3 5
P(A_1) = \frac{20}{50} = \frac{2}{5}, \quad P(A_2) = \frac{30}{50} = \frac{3}{5}
P ( A 1 ) = 50 20 = 5 2 , P ( A 2 ) = 50 30 = 5 3 若第一个人取到黄球,则剩余 49 个球中有 19 个黄球:
P ( B ∣ A 1 ) = 19 49
P(B \mid A_1) = \frac{19}{49}
P ( B ∣ A 1 ) = 49 19 若第一个人取到白球,则剩余 49 个球中有 20 个黄球:
P ( B ∣ A 2 ) = 20 49
P(B \mid A_2) = \frac{20}{49}
P ( B ∣ A 2 ) = 49 20 代入全概率公式:
P ( B ) = 19 49 ⋅ 2 5 + 20 49 ⋅ 3 5
P(B) = \frac{19}{49} \cdot \frac{2}{5} + \frac{20}{49} \cdot \frac{3}{5}
P ( B ) = 49 19 ⋅ 5 2 + 49 20 ⋅ 5 3
P ( B ) = 38 245 + 60 245 = 98 245 = 2 5
P(B) = \frac{38}{245} + \frac{60}{245} = \frac{98}{245} = \frac{2}{5}
P ( B ) = 245 38 + 245 60 = 245 98 = 5 2 因此,第二个人取到黄球的概率为
2 5 \frac{2}{5} 5 2
。
选择题 本题共5小题,每小题3分,满分15分
6 二元函数
f ( x , y ) = { x y x 2 + y 2 , ( x , y ) ≠ ( 0 , 0 ) , 0 , ( x , y ) = ( 0 , 0 ) f(x,y) = \begin{cases}
\frac{xy}{x^2 + y^2}, & (x,y) \ne(0,0), \\
0, & (x,y) = (0,0)
\end{cases} f ( x , y ) = { x 2 + y 2 x y , 0 , ( x , y ) = ( 0 , 0 ) , ( x , y ) = ( 0 , 0 )
在点
( 0 , 0 ) (0,0) ( 0 , 0 )
处
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正确答案:C 【解析】 首先,检查连续性: 考虑沿路径
y = x y = x y = x
接近
( 0 , 0 ) (0,0) ( 0 , 0 )
,有
f ( x , x ) = x ⋅ x x 2 + x 2 = x 2 2 x 2 = 1 2 ,
f(x, x) = \frac{x \cdot x}{x^2 + x^2} = \frac{x^2}{2x^2} = \frac{1}{2},
f ( x , x ) = x 2 + x 2 x ⋅ x = 2 x 2 x 2 = 2 1 , 极限为
1 2 ≠ f ( 0 , 0 ) = 0 \frac{1}{2} \neq f(0,0) = 0 2 1 = f ( 0 , 0 ) = 0
,因此函数在
( 0 , 0 ) (0,0) ( 0 , 0 )
处不连续。
其次,检查偏导数: 由定义,
f x ( 0 , 0 ) = lim h → 0 f ( h , 0 ) − f ( 0 , 0 ) h = lim h → 0 0 h = 0 ,
f_x(0,0) = \lim_{h \to 0} \frac{f(h,0) - f(0,0)}{h} = \lim_{h \to 0} \frac{0}{h} = 0,
f x ( 0 , 0 ) = h → 0 lim h f ( h , 0 ) − f ( 0 , 0 ) = h → 0 lim h 0 = 0 , 同理
f y ( 0 , 0 ) = 0 f_y(0,0) = 0 f y ( 0 , 0 ) = 0
,故偏导数存在。
因此,选项 C 正确。
7 设在区间
[ a , b ] [a,b] [ a , b ]
上
f ( x ) > 0 f(x) > 0 f ( x ) > 0
,
f ′ ( x ) < 0 f'(x) < 0 f ′ ( x ) < 0
,
f ′ ′ ( x ) > 0 f''(x) > 0 f ′′ ( x ) > 0
,令
S 1 = ∫ a b f ( x ) d x , S 2 = f ( b ) ( b − a ) , S 3 = 1 2 [ f ( a ) + f ( b ) ] ( b − a ) , S_1 = \int_a^b f(x)\dx,\quad S_2 = f(b)(b - a),\quad S_3 = \frac{1}{2}[f(a) + f(b)](b - a), S 1 = ∫ a b f ( x ) d x , S 2 = f ( b ) ( b − a ) , S 3 = 2 1 [ f ( a ) + f ( b )] ( b − a ) , 则
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正确答案:B 【解析】 在区间
[ a , b ] [a, b] [ a , b ]
上,
f ′ ( x ) < 0 f'(x) < 0 f ′ ( x ) < 0
,说明函数
f ( x ) f(x) f ( x )
严格递减。 因此,对于任意
x ∈ [ a , b ] x \in [a, b] x ∈ [ a , b ]
,有
f ( x ) ≥ f ( b ) ,
f(x) \geq f(b),
f ( x ) ≥ f ( b ) , 从而
S 1 = ∫ a b f ( x ) d x ≥ ∫ a b f ( b ) d x = f ( b ) ( b − a ) = S 2 .
S_1 = \int_a^b f(x) \, dx \geq \int_a^b f(b) \, dx = f(b)(b - a) = S_2.
S 1 = ∫ a b f ( x ) d x ≥ ∫ a b f ( b ) d x = f ( b ) ( b − a ) = S 2 . 由于函数严格递减,等号不成立,故
S 2 < S 1 .
S_2 < S_1.
S 2 < S 1 . 又因为
f ′ ′ ( x ) > 0 f''(x) > 0 f ′′ ( x ) > 0
,函数
f ( x ) f(x) f ( x )
严格凸,因此图像在连接点
( a , f ( a ) ) (a, f(a)) ( a , f ( a ))
与
( b , f ( b ) ) (b, f(b)) ( b , f ( b ))
的弦之下,即积分
S 1 S_1 S 1
小于梯形面积
S 3 = 1 2 [ f ( a ) + f ( b ) ] ( b − a ) ,
S_3 = \frac{1}{2} \left[ f(a) + f(b) \right](b - a),
S 3 = 2 1 [ f ( a ) + f ( b ) ] ( b − a ) , 故
S 1 < S 3 .
S_1 < S_3.
S 1 < S 3 . 综上,
S 2 < S 1 < S 3 ,
S_2 < S_1 < S_3,
S 2 < S 1 < S 3 , 对应选项 B 。
8 设 F ( x ) = ∫ x x + 2 π e sin t sin t d t \text{设}F(x) = \int_x^{x + 2\pi} \e^{\sin t} \sin t\dt 设 F ( x ) = ∫ x x + 2 π e s i n t sin t d t
,则
F ( x ) F(x) F ( x )
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正确答案:A 【解析】
给定
F ( x ) = ∫ x x + 2 π e sin t sin t d t ,
F(x) = \int_x^{x + 2\pi} e^{\sin t} \sin t \, dt,
F ( x ) = ∫ x x + 2 π e s i n t sin t d t , 由于被积函数
e sin t sin t e^{\sin t} \sin t e s i n t sin t
是以
2 π 2\pi 2 π
为周期的函数,在一个完整周期上的积分与起点
x x x
无关,因此
F ( x ) F(x) F ( x )
是一个常数。
为确定该常数的符号,计算
F ( 0 ) = ∫ 0 2 π e sin t sin t d t .
F(0) = \int_0^{2\pi} e^{\sin t} \sin t \, dt.
F ( 0 ) = ∫ 0 2 π e s i n t sin t d t . 将积分拆分为两部分:
∫ 0 π e sin t sin t d t + ∫ π 2 π e sin t sin t d t .
\int_0^{\pi} e^{\sin t} \sin t \, dt + \int_{\pi}^{2\pi} e^{\sin t} \sin t \, dt.
∫ 0 π e s i n t sin t d t + ∫ π 2 π e s i n t sin t d t . 对第二部分作变量代换
u = t − π u = t - \pi u = t − π
,则
∫ π 2 π e sin t sin t d t = ∫ 0 π e sin ( u + π ) sin ( u + π ) d u = ∫ 0 π − e − sin u sin u d u .
\int_{\pi}^{2\pi} e^{\sin t} \sin t \, dt = \int_0^{\pi} e^{\sin(u + \pi)} \sin(u + \pi) \, du = \int_0^{\pi} -e^{-\sin u} \sin u \, du.
∫ π 2 π e s i n t sin t d t = ∫ 0 π e s i n ( u + π ) sin ( u + π ) d u = ∫ 0 π − e − s i n u sin u d u . 因此,
F ( 0 ) = ∫ 0 π ( e sin t sin t − e − sin t sin t ) d t = ∫ 0 π sin t ( e sin t − e − sin t ) d t .
F(0) = \int_0^{\pi} \left( e^{\sin t} \sin t - e^{-\sin t} \sin t \right) dt = \int_0^{\pi} \sin t \left( e^{\sin t} - e^{-\sin t} \right) dt.
F ( 0 ) = ∫ 0 π ( e s i n t sin t − e − s i n t sin t ) d t = ∫ 0 π sin t ( e s i n t − e − s i n t ) d t . 利用双曲正弦函数
sinh z = e z − e − z 2 \sinh z = \frac{e^z - e^{-z}}{2} sinh z = 2 e z − e − z
,可得
F ( 0 ) = 2 ∫ 0 π sin t ⋅ sinh ( sin t ) d t .
F(0) = 2 \int_0^{\pi} \sin t \cdot \sinh(\sin t) \, dt.
F ( 0 ) = 2 ∫ 0 π sin t ⋅ sinh ( sin t ) d t . 在区间
[ 0 , π ] [0, \pi] [ 0 , π ]
上,
sin t ≥ 0 \sin t \geq 0 sin t ≥ 0
,且当
t ∈ ( 0 , π ) t \in (0, \pi) t ∈ ( 0 , π )
时,
sinh ( sin t ) > 0 \sinh(\sin t) > 0 sinh ( sin t ) > 0
,因此被积函数恒正,积分大于零。
故
F ( x ) F(x) F ( x )
为正常数。
9 设
α 1 = ( a 1 a 2 a 3 ) \alpha_1 =\begin{pmatrix}
a_1 \\
a_2 \\
a_3 \\
\end{pmatrix} α 1 = a 1 a 2 a 3
,
α 2 = ( b 1 b 2 b 3 ) \alpha_2 = \begin{pmatrix}
b_1 \\
b_2 \\
b_3 \\
\end{pmatrix} α 2 = b 1 b 2 b 3
,
α 3 = ( c 1 c 2 c 3 ) \alpha_3 = \begin{pmatrix}
c_1 \\
c_2 \\
c_3 \\
\end{pmatrix} α 3 = c 1 c 2 c 3
,则三条直线
a 1 x + b 1 y + c 1 = 0 , a 2 x + b 2 y + c 2 = 0 , a 3 x + b 3 y + c 3 = 0 a_1 x + b_1 y + c_1 = 0,\quad a_2 x + b_2 y + c_2 = 0,\quad a_3 x + b_3 y + c_3 = 0 a 1 x + b 1 y + c 1 = 0 , a 2 x + b 2 y + c 2 = 0 , a 3 x + b 3 y + c 3 = 0 (其中
a i 2 + b i 2 ≠ 0 , i = 1 , 2 , 3 a_i^2+ b_i^2\ne 0,i = 1,2,3 a i 2 + b i 2 = 0 , i = 1 , 2 , 3
)交于一点的充要条件是
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正确答案:D 【解析】 三条直线交于一点等价于方程组有唯一解,这要求系数矩阵与增广矩阵的秩均为2。向量
α 1 , α 2 , α 3 \alpha_1, \alpha_2, \alpha_3 α 1 , α 2 , α 3
线性相关意味着秩小于3,而
α 1 , α 2 \alpha_1, \alpha_2 α 1 , α 2
线性无关意味着秩为2,确保两条直线相交于一点,且第三条直线经过该点。因此,充要条件是
α 1 , α 2 , α 3 \alpha_1, \alpha_2, \alpha_3 α 1 , α 2 , α 3
线性相关,且
α 1 , α 2 \alpha_1, \alpha_2 α 1 , α 2
线性无关,对应选项 D。
10 设两个相互独立的随机变量
X X X
和
Y Y Y
的方差分别为
4 4 4
和
2 2 2
,则随机变量
3 X − 2 Y 3X - 2Y 3 X − 2 Y
的方差是
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正确答案:D 【解析】 由于
X X X
和
Y Y Y
相互独立,随机变量
3 X − 2 Y 3X - 2Y 3 X − 2 Y
的方差为:
Var ( 3 X − 2 Y ) = 3 2 ⋅ Var ( X ) + ( − 2 ) 2 ⋅ Var ( Y ) = 9 × 4 + 4 × 2 = 36 + 8 = 44.
\begin{aligned}
\text{Var}(3X - 2Y) &= 3^2 \cdot \text{Var}(X) + (-2)^2 \cdot \text{Var}(Y) \\
&= 9 \times 4 + 4 \times 2 \\
&= 36 + 8 = 44.
\end{aligned}
Var ( 3 X − 2 Y ) = 3 2 ⋅ Var ( X ) + ( − 2 ) 2 ⋅ Var ( Y ) = 9 × 4 + 4 × 2 = 36 + 8 = 44. 计算题 本题共3小题,每小题5分,满分15分
11 计算
I = ∭ Ω ( x 2 + y 2 ) d V I = \iiint_{\Omega}(x^2 + y^2) \d V I = ∭ Ω ( x 2 + y 2 ) d V
,其中
Ω \Omega Ω
为平面曲线
{ y 2 = 2 z , x = 0 \begin{cases}
y^2 = 2z, \\
x = 0
\end{cases} { y 2 = 2 z , x = 0
绕
z z z
轴旋转一周形成的曲面与平面
z = 8 z = 8 z = 8
所围成的区域.
【答案】
1024 π 3 \frac{1024\pi}{3} 3 1024 π
【解析】
积分区域
Ω \Omega Ω
是由曲线
{ y 2 = 2 z x = 0
\begin{cases}
y^2 = 2z \\
x = 0
\end{cases}
{ y 2 = 2 z x = 0 绕
z z z
-轴旋转所形成的曲面与平面
z = 8 z = 8 z = 8
所围成。旋转曲面的方程为
x 2 + y 2 = 2 z ,
x^2 + y^2 = 2z,
x 2 + y 2 = 2 z , 即
其中
r = x 2 + y 2 r = \sqrt{x^2 + y^2} r = x 2 + y 2
。该曲面与平面
z = 8 z = 8 z = 8
相交于圆
r = 4 r = 4 r = 4
。
使用柱坐标计算积分:令
x = r cos θ , y = r sin θ , z = z ,
x = r\cos\theta,\quad y = r\sin\theta,\quad z = z,
x = r cos θ , y = r sin θ , z = z , 则
x 2 + y 2 = r 2 x^2 + y^2 = r^2 x 2 + y 2 = r 2
,体积元素
d V = r d r d θ d z .
\mathrm{d}V = r\,\mathrm{d}r\,\mathrm{d}\theta\,\mathrm{d}z.
d V = r d r d θ d z . 积分变为
I = ∭ Ω r 2 ⋅ r d r d θ d z = ∫ 0 2 π d θ ∫ 0 4 d r ∫ z = r 2 2 8 r 3 d z .
I = \iiint_{\Omega} r^2 \cdot r \,\mathrm{d}r\,\mathrm{d}\theta\,\mathrm{d}z
= \int_{0}^{2\pi} \mathrm{d}\theta \int_{0}^{4} \mathrm{d}r \int_{z = \frac{r^2}{2}}^{8} r^3 \,\mathrm{d}z.
I = ∭ Ω r 2 ⋅ r d r d θ d z = ∫ 0 2 π d θ ∫ 0 4 d r ∫ z = 2 r 2 8 r 3 d z . 先对
z z z
积分:
∫ r 2 2 8 d z = 8 − r 2 2 ,
\int_{\frac{r^2}{2}}^{8} \mathrm{d}z = 8 - \frac{r^2}{2},
∫ 2 r 2 8 d z = 8 − 2 r 2 , 因此
I = ∫ 0 2 π d θ ∫ 0 4 r 3 ( 8 − r 2 2 ) d r = 2 π ∫ 0 4 ( 8 r 3 − 1 2 r 5 ) d r .
I = \int_{0}^{2\pi} \mathrm{d}\theta \int_{0}^{4} r^3 \left( 8 - \frac{r^2}{2} \right) \mathrm{d}r
= 2\pi \int_{0}^{4} \left( 8r^3 - \frac{1}{2} r^5 \right) \mathrm{d}r.
I = ∫ 0 2 π d θ ∫ 0 4 r 3 ( 8 − 2 r 2 ) d r = 2 π ∫ 0 4 ( 8 r 3 − 2 1 r 5 ) d r . 计算对
r r r
的积分:
∫ 0 4 ( 8 r 3 − 1 2 r 5 ) d r = [ 2 r 4 − r 6 12 ] 0 4 = 2 ⋅ 256 − 4096 12 = 512 − 1024 3 = 512 3 .
\int_{0}^{4} \left( 8r^3 - \frac{1}{2} r^5 \right) \mathrm{d}r
= \left[ 2r^4 - \frac{r^6}{12} \right]_{0}^{4}
= 2 \cdot 256 - \frac{4096}{12}
= 512 - \frac{1024}{3}
= \frac{512}{3}.
∫ 0 4 ( 8 r 3 − 2 1 r 5 ) d r = [ 2 r 4 − 12 r 6 ] 0 4 = 2 ⋅ 256 − 12 4096 = 512 − 3 1024 = 3 512 . 于是
I = 2 π ⋅ 512 3 = 1024 π 3 .
I = 2\pi \cdot \frac{512}{3} = \frac{1024\pi}{3}.
I = 2 π ⋅ 3 512 = 3 1024 π . 另一种方法 :交换积分次序,以
z z z
为外层变量:
I = ∫ 0 2 π d θ ∫ 0 8 d z ∫ 0 2 z r 3 d r = 2 π ∫ 0 8 [ r 4 4 ] 0 2 z d z = 2 π ∫ 0 8 z 2 d z = 2 π ⋅ 512 3 = 1024 π 3 ,
I = \int_{0}^{2\pi} \mathrm{d}\theta \int_{0}^{8} \mathrm{d}z \int_{0}^{\sqrt{2z}} r^3 \,\mathrm{d}r
= 2\pi \int_{0}^{8} \left[ \frac{r^4}{4} \right]_{0}^{\sqrt{2z}} \mathrm{d}z
= 2\pi \int_{0}^{8} z^2 \,\mathrm{d}z
= 2\pi \cdot \frac{512}{3}
= \frac{1024\pi}{3},
I = ∫ 0 2 π d θ ∫ 0 8 d z ∫ 0 2 z r 3 d r = 2 π ∫ 0 8 [ 4 r 4 ] 0 2 z d z = 2 π ∫ 0 8 z 2 d z = 2 π ⋅ 3 512 = 3 1024 π , 结果一致。
12 计算曲线积分
∮ C ( z − y ) d x + ( x − z ) d y + ( x − y ) d z \oint_C (z - y)\dx + (x - z)\dy + (x - y)\dz ∮ C ( z − y ) d x + ( x − z ) d y + ( x − y ) d z
,其中
C C C
是曲线
{ x 2 + y 2 = 1 , x − y + z = 2 , \begin{cases}
x^2 + y^2 = 1, \\
x - y + z = 2,
\end{cases} { x 2 + y 2 = 1 , x − y + z = 2 ,
从
z z z
轴正向往
z z z
轴负向看,
C C C
的方向是顺时针的.
【答案】
− 2 π -2\pi − 2 π
【解析】
曲线积分
∮ C ( z − y ) d x + ( x − z ) d y + ( x − y ) d z \oint_C (z - y) \, dx + (x - z) \, dy + (x - y) \, dz ∮ C ( z − y ) d x + ( x − z ) d y + ( x − y ) d z
,其中
C C C
是曲线
{ x 2 + y 2 = 1 , x − y + z = 2 \begin{cases} x^2 + y^2 = 1, \\ x - y + z = 2 \end{cases} { x 2 + y 2 = 1 , x − y + z = 2
,从
z z z
轴正向往负向看方向为顺时针。
使用斯托克斯定理,将曲线积分转化为曲面积分。设
F = ( z − y , x − z , x − y ) \mathbf{F} = (z - y, x - z, x - y) F = ( z − y , x − z , x − y )
,则旋度
∇ × F = ( ∂ R ∂ y − ∂ Q ∂ z , ∂ P ∂ z − ∂ R ∂ x , ∂ Q ∂ x − ∂ P ∂ y ) = ( 0 , 0 , 2 ) \nabla \times \mathbf{F} = \left( \frac{\partial R}{\partial y} - \frac{\partial Q}{\partial z}, \frac{\partial P}{\partial z} - \frac{\partial R}{\partial x}, \frac{\partial Q}{\partial x} - \frac{\partial P}{\partial y} \right) = (0, 0, 2) ∇ × F = ( ∂ y ∂ R − ∂ z ∂ Q , ∂ z ∂ P − ∂ x ∂ R , ∂ x ∂ Q − ∂ y ∂ P ) = ( 0 , 0 , 2 )
。
选取曲面
S S S
为平面
x − y + z = 2 x - y + z = 2 x − y + z = 2
上满足
x 2 + y 2 ≤ 1 x^2 + y^2 \leq 1 x 2 + y 2 ≤ 1
的部分,根据曲线方向(从
z z z
轴正向往负向看顺时针),曲面的法向量应指向
z z z
轴负方向。曲面
S S S
的参数化为
z = 2 − x + y z = 2 - x + y z = 2 − x + y
,向下法向量对应的
d S = ( − 1 , 1 , − 1 ) d x d y d\mathbf{S} = (-1, 1, -1) \, dx \, dy d S = ( − 1 , 1 , − 1 ) d x d y
。
计算通量积分:
∬ S ( ∇ × F ) ⋅ d S = ∬ S ( 0 , 0 , 2 ) ⋅ ( − 1 , 1 , − 1 ) d x d y = ∬ S − 2 d x d y . \iint_S (\nabla \times \mathbf{F}) \cdot d\mathbf{S} = \iint_S (0, 0, 2) \cdot (-1, 1, -1) \, dx \, dy = \iint_S -2 \, dx \, dy. ∬ S ( ∇ × F ) ⋅ d S = ∬ S ( 0 , 0 , 2 ) ⋅ ( − 1 , 1 , − 1 ) d x d y = ∬ S − 2 d x d y . 投影区域
D D D
为
x 2 + y 2 ≤ 1 x^2 + y^2 \leq 1 x 2 + y 2 ≤ 1
,面积为
π \pi π
,因此积分值为
− 2 × π = − 2 π -2 \times \pi = -2\pi − 2 × π = − 2 π
。
也可直接参数化曲线验证:令
x = cos t x = \cos t x = cos t
,
y = − sin t y = -\sin t y = − sin t
,
z = 2 − cos t − sin t z = 2 - \cos t - \sin t z = 2 − cos t − sin t
,
t ∈ [ 0 , 2 π ] t \in [0, 2\pi] t ∈ [ 0 , 2 π ]
,代入曲线积分计算得
− 2 π -2\pi − 2 π
,结果一致。
故曲线积分为
− 2 π -2\pi − 2 π
。
13 在某一人群中推广新技术是通过其中已掌握新技术的人进行的.
设该人群的总人数为
N N N
,在
t = 0 t = 0 t = 0
时刻已掌握新技术的人数为
x 0 x_0 x 0
,
在任意时刻
t t t
已掌握新技术的人数为
x ( t ) x(t) x ( t )
(将
x ( t ) x(t) x ( t )
视为连续可微变量),
其变化率与已掌握新技术人数和未掌握新技术人数之积成正比,比例常数
k > 0 k > 0 k > 0
,求
x ( t ) x(t) x ( t )
.
【答案】
x ( t ) = N 1 + ( N − x 0 x 0 ) e − N k t x(t) = \frac{N}{1 + \left( \frac{N - x_0}{x_0} \right) e^{-N k t}} x ( t ) = 1 + ( x 0 N − x 0 ) e − N k t N 【解析】
根据题意,已掌握新技术人数
x ( t ) x(t) x ( t )
的变化率与已掌握人数和未掌握人数之积成正比,即:
d x d t = k x ( N − x ) \frac{dx}{dt} = k x (N - x) d t d x = k x ( N − x ) 其中
k > 0 k > 0 k > 0
为比例常数。这是一个可分离变量的微分方程。将方程改写为:
d x x ( N − x ) = k d t \frac{dx}{x (N - x)} = k \, dt x ( N − x ) d x = k d t 对两边积分:
∫ 1 x ( N − x ) d x = ∫ k d t \int \frac{1}{x (N - x)} \, dx = \int k \, dt ∫ x ( N − x ) 1 d x = ∫ k d t 左边积分通过部分分式分解:
1 x ( N − x ) = 1 N ( 1 x + 1 N − x ) \frac{1}{x (N - x)} = \frac{1}{N} \left( \frac{1}{x} + \frac{1}{N - x} \right) x ( N − x ) 1 = N 1 ( x 1 + N − x 1 ) 因此:
1 N ∫ ( 1 x + 1 N − x ) d x = k ∫ d t \frac{1}{N} \int \left( \frac{1}{x} + \frac{1}{N - x} \right) dx = k \int dt N 1 ∫ ( x 1 + N − x 1 ) d x = k ∫ d t 积分得:
1 N ( ln x − ln ( N − x ) ) = k t + C \frac{1}{N} \left( \ln x - \ln (N - x) \right) = k t + C N 1 ( ln x − ln ( N − x ) ) = k t + C 即:
1 N ln ( x N − x ) = k t + C \frac{1}{N} \ln \left( \frac{x}{N - x} \right) = k t + C N 1 ln ( N − x x ) = k t + C 代入初始条件
t = 0 t = 0 t = 0
时
x = x 0 x = x_0 x = x 0
:
1 N ln ( x 0 N − x 0 ) = C \frac{1}{N} \ln \left( \frac{x_0}{N - x_0} \right) = C N 1 ln ( N − x 0 x 0 ) = C 所以:
1 N ln ( x N − x ) = k t + 1 N ln ( x 0 N − x 0 ) \frac{1}{N} \ln \left( \frac{x}{N - x} \right) = k t + \frac{1}{N} \ln \left( \frac{x_0}{N - x_0} \right) N 1 ln ( N − x x ) = k t + N 1 ln ( N − x 0 x 0 ) 两边乘以
N N N
:
ln ( x N − x ) = N k t + ln ( x 0 N − x 0 ) \ln \left( \frac{x}{N - x} \right) = N k t + \ln \left( \frac{x_0}{N - x_0} \right) ln ( N − x x ) = N k t + ln ( N − x 0 x 0 ) 取指数:
x N − x = x 0 N − x 0 e N k t \frac{x}{N - x} = \frac{x_0}{N - x_0} e^{N k t} N − x x = N − x 0 x 0 e N k t 解出
x x x
:
x = N 1 + ( N − x 0 x 0 ) e − N k t x = \frac{N}{1 + \left( \frac{N - x_0}{x_0} \right) e^{-N k t}} x = 1 + ( x 0 N − x 0 ) e − N k t N 此即
x ( t ) x(t) x ( t )
的表达式。
计算题 本题共2小题,第(1)小题6分,第(2)小题7分,满分13分
14 设直线
L : { x + y + b = 0 , x + a y − z − 3 = 0 L:\begin{cases}
x + y + b = 0, \\
x + ay - z - 3 = 0
\end{cases} L : { x + y + b = 0 , x + a y − z − 3 = 0
在平面
Π \Pi Π
上,且平面
Π \Pi Π
与曲面
z = x 2 + y 2 z = x^2 + y^2 z = x 2 + y 2
相切于点
( 1 , − 2 , 5 ) (1, - 2,5) ( 1 , − 2 , 5 )
,求
a , b a,b a , b
之值.
【答案】 a = − 5 a = -5 a = − 5
,
b = − 2 b = -2 b = − 2
【解析】 曲面
z = x 2 + y 2 z = x^2 + y^2 z = x 2 + y 2
在点
( 1 , − 2 , 5 ) (1, -2, 5) ( 1 , − 2 , 5 )
处的切平面方程为
z − 5 = 2 ( x − 1 ) − 4 ( y + 2 ) z - 5 = 2(x - 1) - 4(y + 2) z − 5 = 2 ( x − 1 ) − 4 ( y + 2 )
,即
2 x − 4 y − z − 5 = 0 2x - 4y - z - 5 = 0 2 x − 4 y − z − 5 = 0
。 直线
L L L
由方程
x + y + b = 0 x + y + b = 0 x + y + b = 0
和
x + a y − z − 3 = 0 x + ay - z - 3 = 0 x + a y − z − 3 = 0
定义,且位于切平面上。因此,切平面方程可表示为这两个方程的线性组合:
λ ( x + y + b ) + μ ( x + a y − z − 3 ) = 2 x − 4 y − z − 5 \lambda(x + y + b) + \mu(x + ay - z - 3) = 2x - 4y - z - 5 λ ( x + y + b ) + μ ( x + a y − z − 3 ) = 2 x − 4 y − z − 5 比较系数:
x x x
系数:
λ + μ = 2 \lambda + \mu = 2 λ + μ = 2 y y y
系数:
λ + a μ = − 4 \lambda + a\mu = -4 λ + a μ = − 4 z z z
系数:
− μ = − 1 -\mu = -1 − μ = − 1
,解得
μ = 1 \mu = 1 μ = 1 代入
μ = 1 \mu = 1 μ = 1
:λ + 1 = 2 \lambda + 1 = 2 λ + 1 = 2
,解得
λ = 1 \lambda = 1 λ = 1 1 + a ⋅ 1 = − 4 1 + a \cdot 1 = -4 1 + a ⋅ 1 = − 4
,解得
a = − 5 a = -5 a = − 5 常数项:
λ b − 3 μ = − 5 \lambda b - 3\mu = -5 λb − 3 μ = − 5
,即
1 ⋅ b − 3 ⋅ 1 = − 5 1 \cdot b - 3 \cdot 1 = -5 1 ⋅ b − 3 ⋅ 1 = − 5
,解得
b = − 2 b = -2 b = − 2 因此,
a = − 5 a = -5 a = − 5
,
b = − 2 b = -2 b = − 2
。 15 设函数
f ( u ) f(u) f ( u )
具有二阶连续导数,而
z = f ( e x sin y ) z = f(\e^x\sin y) z = f ( e x sin y )
满足方程
∂ 2 z ∂ x 2 + ∂ 2 z ∂ y 2 = e 2 x z \frac{\pd^2 z}{\pd x^2} + \frac{\pd^2 z}{\pd y^2} = \e^{2x} z ∂ x 2 ∂ 2 z + ∂ y 2 ∂ 2 z = e 2 x z
,求
f ( u ) f(u) f ( u )
.
【答案】 f ( u ) = C 1 e u + C 2 e − u f(u) = C_1 e^u + C_2 e^{-u} f ( u ) = C 1 e u + C 2 e − u
,其中
C 1 C_1 C 1
和
C 2 C_2 C 2
为任意常数。
【解析】 设
u = e x sin y u = e^x \sin y u = e x sin y
,则
z = f ( u ) z = f(u) z = f ( u )
。计算一阶偏导数:
∂ z ∂ x = f ′ ( u ) ∂ u ∂ x = f ′ ( u ) e x sin y = f ′ ( u ) u , \frac{\partial z}{\partial x} = f'(u) \frac{\partial u}{\partial x} = f'(u) e^x \sin y = f'(u) u, ∂ x ∂ z = f ′ ( u ) ∂ x ∂ u = f ′ ( u ) e x sin y = f ′ ( u ) u ,
∂ z ∂ y = f ′ ( u ) ∂ u ∂ y = f ′ ( u ) e x cos y . \frac{\partial z}{\partial y} = f'(u) \frac{\partial u}{\partial y} = f'(u) e^x \cos y. ∂ y ∂ z = f ′ ( u ) ∂ y ∂ u = f ′ ( u ) e x cos y . 计算二阶偏导数:
∂ 2 z ∂ x 2 = ∂ ∂ x [ f ′ ( u ) e x sin y ] = f ′ ′ ( u ) ( e x sin y ) 2 + f ′ ( u ) e x sin y = f ′ ′ ( u ) u 2 + f ′ ( u ) u , \frac{\partial^2 z}{\partial x^2} = \frac{\partial}{\partial x} [f'(u) e^x \sin y] = f''(u) (e^x \sin y)^2 + f'(u) e^x \sin y = f''(u) u^2 + f'(u) u, ∂ x 2 ∂ 2 z = ∂ x ∂ [ f ′ ( u ) e x sin y ] = f ′′ ( u ) ( e x sin y ) 2 + f ′ ( u ) e x sin y = f ′′ ( u ) u 2 + f ′ ( u ) u ,
∂ 2 z ∂ y 2 = ∂ ∂ y [ f ′ ( u ) e x cos y ] = f ′ ′ ( u ) ( e x cos y ) 2 − f ′ ( u ) e x sin y = f ′ ′ ( u ) e 2 x cos 2 y − f ′ ( u ) u . \frac{\partial^2 z}{\partial y^2} = \frac{\partial}{\partial y} [f'(u) e^x \cos y] = f''(u) (e^x \cos y)^2 - f'(u) e^x \sin y = f''(u) e^{2x} \cos^2 y - f'(u) u. ∂ y 2 ∂ 2 z = ∂ y ∂ [ f ′ ( u ) e x cos y ] = f ′′ ( u ) ( e x cos y ) 2 − f ′ ( u ) e x sin y = f ′′ ( u ) e 2 x cos 2 y − f ′ ( u ) u . 将二阶偏导数相加:
∂ 2 z ∂ x 2 + ∂ 2 z ∂ y 2 = f ′ ′ ( u ) u 2 + f ′ ( u ) u + f ′ ′ ( u ) e 2 x cos 2 y − f ′ ( u ) u = f ′ ′ ( u ) ( u 2 + e 2 x cos 2 y ) . \frac{\partial^2 z}{\partial x^2} + \frac{\partial^2 z}{\partial y^2} = f''(u) u^2 + f'(u) u + f''(u) e^{2x} \cos^2 y - f'(u) u = f''(u) (u^2 + e^{2x} \cos^2 y). ∂ x 2 ∂ 2 z + ∂ y 2 ∂ 2 z = f ′′ ( u ) u 2 + f ′ ( u ) u + f ′′ ( u ) e 2 x cos 2 y − f ′ ( u ) u = f ′′ ( u ) ( u 2 + e 2 x cos 2 y ) . 代入
u 2 = e 2 x sin 2 y u^2 = e^{2x} \sin^2 y u 2 = e 2 x sin 2 y
,得:
u 2 + e 2 x cos 2 y = e 2 x ( sin 2 y + cos 2 y ) = e 2 x . u^2 + e^{2x} \cos^2 y = e^{2x} (\sin^2 y + \cos^2 y) = e^{2x}. u 2 + e 2 x cos 2 y = e 2 x ( sin 2 y + cos 2 y ) = e 2 x . 所以,
∂ 2 z ∂ x 2 + ∂ 2 z ∂ y 2 = f ′ ′ ( u ) e 2 x . \frac{\partial^2 z}{\partial x^2} + \frac{\partial^2 z}{\partial y^2} = f''(u) e^{2x}. ∂ x 2 ∂ 2 z + ∂ y 2 ∂ 2 z = f ′′ ( u ) e 2 x . 由给定方程
∂ 2 z ∂ x 2 + ∂ 2 z ∂ y 2 = e 2 x z \frac{\partial^2 z}{\partial x^2} + \frac{\partial^2 z}{\partial y^2} = e^{2x} z ∂ x 2 ∂ 2 z + ∂ y 2 ∂ 2 z = e 2 x z
和
z = f ( u ) z = f(u) z = f ( u )
,得:
f ′ ′ ( u ) e 2 x = e 2 x f ( u ) . f''(u) e^{2x} = e^{2x} f(u). f ′′ ( u ) e 2 x = e 2 x f ( u ) . 除以
e 2 x e^{2x} e 2 x
(因
e 2 x ≠ 0 e^{2x} \neq 0 e 2 x = 0
),得:
f ′ ′ ( u ) = f ( u ) . f''(u) = f(u). f ′′ ( u ) = f ( u ) . 解此微分方程: 特征方程为
r 2 − 1 = 0 r^2 - 1 = 0 r 2 − 1 = 0
,根为
r = ± 1 r = \pm 1 r = ± 1
,故通解为
f ( u ) = C 1 e u + C 2 e − u , f(u) = C_1 e^u + C_2 e^{-u}, f ( u ) = C 1 e u + C 2 e − u , 其中
C 1 C_1 C 1
和
C 2 C_2 C 2
为任意常数。
解答题 16 设
f ( x ) f(x) f ( x )
连续,
φ ( x ) = ∫ 0 1 f ( x t ) d t \varphi (x) = \int_0^1f(xt) \dt φ ( x ) = ∫ 0 1 f ( x t ) d t
,且
lim x → 0 f ( x ) x = A \lim_{x \to 0} \frac{f(x)}{x} = A lim x → 0 x f ( x ) = A
(
A A A
为常数),求
φ ′ ( x ) \varphi'(x) φ ′ ( x )
并讨论
φ ′ ( x ) \varphi'(x) φ ′ ( x )
在
x = 0 x = 0 x = 0
处的连续性.
【答案】
φ ′ ( x ) = 1 x f ( x ) − 1 x 2 ∫ 0 x f ( u ) d u \varphi'(x) = \frac{1}{x} f(x) - \frac{1}{x^2} \int_0^x f(u) \, du φ ′ ( x ) = x 1 f ( x ) − x 2 1 ∫ 0 x f ( u ) d u
(当
x ≠ 0 x \neq 0 x = 0
),且
φ ′ ( 0 ) = A 2 \varphi'(0) = \frac{A}{2} φ ′ ( 0 ) = 2 A
,
φ ′ ( x ) \varphi'(x) φ ′ ( x )
在
x = 0 x=0 x = 0
处连续。
【解析】
由
φ ( x ) = ∫ 0 1 f ( x t ) d t \varphi(x) = \int_0^1 f(xt) \, dt φ ( x ) = ∫ 0 1 f ( x t ) d t
,当
x ≠ 0 x \neq 0 x = 0
时,通过变量代换
u = x t u = xt u = x t
,得
φ ( x ) = 1 x ∫ 0 x f ( u ) d u \varphi(x) = \frac{1}{x} \int_0^x f(u) \, du φ ( x ) = x 1 ∫ 0 x f ( u ) d u
。对其求导,有
φ ′ ( x ) = d d x ( 1 x ∫ 0 x f ( u ) d u ) = − 1 x 2 ∫ 0 x f ( u ) d u + 1 x f ( x ) \varphi'(x) = \frac{d}{dx} \left( \frac{1}{x} \int_0^x f(u) \, du \right) = -\frac{1}{x^2} \int_0^x f(u) \, du + \frac{1}{x} f(x) φ ′ ( x ) = d x d ( x 1 ∫ 0 x f ( u ) d u ) = − x 2 1 ∫ 0 x f ( u ) d u + x 1 f ( x ) 当
x = 0 x = 0 x = 0
时,由导数定义:
φ ′ ( 0 ) = lim x → 0 φ ( x ) − φ ( 0 ) x = lim x → 0 ∫ 0 1 f ( x t ) d t x \varphi'(0) = \lim_{x \to 0} \frac{\varphi(x) - \varphi(0)}{x} = \lim_{x \to 0} \frac{\int_0^1 f(xt) \, dt}{x} φ ′ ( 0 ) = x → 0 lim x φ ( x ) − φ ( 0 ) = x → 0 lim x ∫ 0 1 f ( x t ) d t 由变量代换
∫ 0 1 f ( x t ) d t = 1 x ∫ 0 x f ( u ) d u \int_0^1 f(xt) \, dt = \frac{1}{x} \int_0^x f(u) \, du ∫ 0 1 f ( x t ) d t = x 1 ∫ 0 x f ( u ) d u
,得
φ ′ ( 0 ) = lim x → 0 1 x 2 ∫ 0 x f ( u ) d u = lim x → 0 f ( x ) 2 x = A 2 \varphi'(0) = \lim_{x \to 0} \frac{1}{x^2} \int_0^x f(u) \, du = \lim_{x \to 0} \frac{f(x)}{2x} = \frac{A}{2} φ ′ ( 0 ) = x → 0 lim x 2 1 ∫ 0 x f ( u ) d u = x → 0 lim 2 x f ( x ) = 2 A 其中最后一步使用了洛必达法则。 为讨论
φ ′ ( x ) \varphi'(x) φ ′ ( x )
在
x = 0 x=0 x = 0
处的连续性,计算
lim x → 0 φ ′ ( x ) = lim x → 0 ( 1 x f ( x ) − 1 x 2 ∫ 0 x f ( u ) d u ) = A − A 2 = A 2 = φ ′ ( 0 ) \lim_{x \to 0} \varphi'(x) = \lim_{x \to 0} \left( \frac{1}{x} f(x) - \frac{1}{x^2} \int_0^x f(u) \, du \right) = A - \frac{A}{2} = \frac{A}{2} = \varphi'(0) x → 0 lim φ ′ ( x ) = x → 0 lim ( x 1 f ( x ) − x 2 1 ∫ 0 x f ( u ) d u ) = A − 2 A = 2 A = φ ′ ( 0 ) 因此
φ ′ ( x ) \varphi'(x) φ ′ ( x )
在
x = 0 x=0 x = 0
处连续。
17 设
a 1 = 2 , a n + 1 = 1 2 ( a n + 1 a n ) , n = 1 , 2 , ⋯ a_1 = 2,a_{n + 1} = \frac{1}{2}\left(a_n + \frac{1}{a_n} \right),n = 1,2, \cdots a 1 = 2 , a n + 1 = 2 1 ( a n + a n 1 ) , n = 1 , 2 , ⋯
,证明:
(1)
lim n → ∞ a n \lim_{n \to \infty} a_n lim n → ∞ a n
存在;
(2) 级数
∑ n = 1 ∞ ( a n a n + 1 − 1 ) \sum_{n = 1}^{\infty}\left(\frac{a_n}{a_{n + 1}} - 1 \right) ∑ n = 1 ∞ ( a n + 1 a n − 1 )
收敛.
【答案】 (1)
lim n → ∞ a n \lim_{n \to \infty} a_n lim n → ∞ a n
存在且等于 1。 (2) 级数
∑ n = 1 ∞ ( a n a n + 1 − 1 ) \sum_{n=1}^{\infty} \left( \frac{a_n}{a_{n+1}} - 1 \right) ∑ n = 1 ∞ ( a n + 1 a n − 1 )
收敛。
【解析】 (1) 首先,由
a 1 = 2 > 0 a_1 = 2 > 0 a 1 = 2 > 0
及递推关系
a n + 1 = 1 2 ( a n + 1 a n ) a_{n+1} = \frac{1}{2} \left( a_n + \frac{1}{a_n} \right) a n + 1 = 2 1 ( a n + a n 1 )
,通过数学归纳法可知所有
a n > 0 a_n > 0 a n > 0
。进一步,由算术-几何平均不等式,有
a n + 1 a n ≥ 2 a_n + \frac{1}{a_n} \geq 2 a n + a n 1 ≥ 2
,故
a n + 1 ≥ 1 a_{n+1} \geq 1 a n + 1 ≥ 1
,即序列有下界。 考虑差值
a n + 1 − a n = 1 2 ( 1 a n − a n ) = 1 2 ⋅ 1 − a n 2 a n a_{n+1} - a_n = \frac{1}{2} \left( \frac{1}{a_n} - a_n \right) = \frac{1}{2} \cdot \frac{1 - a_n^2}{a_n} a n + 1 − a n = 2 1 ( a n 1 − a n ) = 2 1 ⋅ a n 1 − a n 2
。由于
a n ≥ 1 a_n \geq 1 a n ≥ 1
,有
1 − a n 2 ≤ 0 1 - a_n^2 \leq 0 1 − a n 2 ≤ 0
,故
a n + 1 − a n ≤ 0 a_{n+1} - a_n \leq 0 a n + 1 − a n ≤ 0
,即序列单调递减。 单调递减有下界的序列必有极限,设
lim n → ∞ a n = L \lim_{n \to \infty} a_n = L lim n → ∞ a n = L
。对递推公式取极限得
L = 1 2 ( L + 1 L ) L = \frac{1}{2} \left( L + \frac{1}{L} \right) L = 2 1 ( L + L 1 )
,解得
L 2 = 1 L^2 = 1 L 2 = 1
。因
a n ≥ 1 a_n \geq 1 a n ≥ 1
,故
L = 1 L = 1 L = 1
。因此
lim n → ∞ a n = 1 \lim_{n \to \infty} a_n = 1 lim n → ∞ a n = 1
。
(2) 考虑级数
∑ n = 1 ∞ ( a n a n + 1 − 1 ) \sum_{n=1}^{\infty} \left( \frac{a_n}{a_{n+1}} - 1 \right) ∑ n = 1 ∞ ( a n + 1 a n − 1 )
。由递推关系,
a n a n + 1 = a n 1 2 ( a n + 1 a n ) = 2 a n a n + 1 a n = 2 a n 2 a n 2 + 1 , \frac{a_n}{a_{n+1}} = \frac{a_n}{\frac{1}{2} \left( a_n + \frac{1}{a_n} \right)} = \frac{2a_n}{a_n + \frac{1}{a_n}} = \frac{2a_n^2}{a_n^2 + 1}, a n + 1 a n = 2 1 ( a n + a n 1 ) a n = a n + a n 1 2 a n = a n 2 + 1 2 a n 2 , 故
a n a n + 1 − 1 = 2 a n 2 a n 2 + 1 − 1 = a n 2 − 1 a n 2 + 1 . \frac{a_n}{a_{n+1}} - 1 = \frac{2a_n^2}{a_n^2 + 1} - 1 = \frac{a_n^2 - 1}{a_n^2 + 1}. a n + 1 a n − 1 = a n 2 + 1 2 a n 2 − 1 = a n 2 + 1 a n 2 − 1 . 令
b n = a n 2 − 1 a n 2 + 1 b_n = \frac{a_n^2 - 1}{a_n^2 + 1} b n = a n 2 + 1 a n 2 − 1
,需证
∑ b n \sum b_n ∑ b n
收敛。 由
a n → 1 a_n \to 1 a n → 1
,定义
c n = a n − 1 c_n = a_n - 1 c n = a n − 1
,则
c n > 0 c_n > 0 c n > 0
且
c n → 0 c_n \to 0 c n → 0
。由递推关系,
a n + 1 − 1 = 1 2 ( a n + 1 a n ) − 1 = 1 2 ⋅ ( a n − 1 ) 2 a n , a_{n+1} - 1 = \frac{1}{2} \left( a_n + \frac{1}{a_n} \right) - 1 = \frac{1}{2} \cdot \frac{(a_n - 1)^2}{a_n}, a n + 1 − 1 = 2 1 ( a n + a n 1 ) − 1 = 2 1 ⋅ a n ( a n − 1 ) 2 , 即
c n + 1 = 1 2 ⋅ c n 2 1 + c n ≤ 1 2 c n 2 , c_{n+1} = \frac{1}{2} \cdot \frac{c_n^2}{1 + c_n} \leq \frac{1}{2} c_n^2, c n + 1 = 2 1 ⋅ 1 + c n c n 2 ≤ 2 1 c n 2 , 其中利用了
1 + c n ≥ 1 1 + c_n \geq 1 1 + c n ≥ 1
。 通过数学归纳法可证
c n ≤ 1 2 2 n − 1 − 1 c_n \leq \frac{1}{2^{2^{n-1} - 1}} c n ≤ 2 2 n − 1 − 1 1
对于
n ≥ 1 n \geq 1 n ≥ 1
成立: 当
n = 1 n=1 n = 1
,
c 1 = 1 = 1 2 0 c_1 = 1 = \frac{1}{2^0} c 1 = 1 = 2 0 1
; 假设
c n ≤ 1 2 2 n − 1 − 1 c_n \leq \frac{1}{2^{2^{n-1} - 1}} c n ≤ 2 2 n − 1 − 1 1
,则
c n + 1 ≤ 1 2 c n 2 ≤ 1 2 ( 1 2 2 n − 1 − 1 ) 2 = 1 2 2 n − 1 = 1 2 2 ( n + 1 ) − 1 − 1 , c_{n+1} \leq \frac{1}{2} c_n^2 \leq \frac{1}{2} \left( \frac{1}{2^{2^{n-1} - 1}} \right)^2 = \frac{1}{2^{2^n - 1}} = \frac{1}{2^{2^{(n+1)-1} - 1}}, c n + 1 ≤ 2 1 c n 2 ≤ 2 1 ( 2 2 n − 1 − 1 1 ) 2 = 2 2 n − 1 1 = 2 2 ( n + 1 ) − 1 − 1 1 , 故成立。因此
∑ c n \sum c_n ∑ c n
收敛。 现在证明
b n ≤ c n b_n \leq c_n b n ≤ c n
。考虑函数
f ( x ) = x 2 − 1 x 2 + 1 − ( x − 1 ) f(x) = \frac{x^2 - 1}{x^2 + 1} - (x - 1) f ( x ) = x 2 + 1 x 2 − 1 − ( x − 1 )
for
x ≥ 1 x \geq 1 x ≥ 1
。 有
f ( 1 ) = 0 f(1) = 0 f ( 1 ) = 0
,且
f ′ ( x ) = 4 x ( x 2 + 1 ) 2 − 1. f'(x) = \frac{4x}{(x^2 + 1)^2} - 1. f ′ ( x ) = ( x 2 + 1 ) 2 4 x − 1. 对于
x > 1 x > 1 x > 1
,有
( x 2 + 1 ) 2 ≥ 4 (x^2 + 1)^2 \geq 4 ( x 2 + 1 ) 2 ≥ 4
,故
4 x ( x 2 + 1 ) 2 ≤ x ≤ 1 \frac{4x}{(x^2 + 1)^2} \leq x \leq 1 ( x 2 + 1 ) 2 4 x ≤ x ≤ 1
(当
x > 1 x > 1 x > 1
时严格小于),所以
f ′ ( x ) < 0 f'(x) < 0 f ′ ( x ) < 0
,即
f ( x ) ≤ 0 f(x) \leq 0 f ( x ) ≤ 0
,因此
b n ≤ c n b_n \leq c_n b n ≤ c n
。 由比较判别法,
∑ b n \sum b_n ∑ b n
收敛,即级数
∑ n = 1 ∞ ( a n a n + 1 − 1 ) \sum_{n=1}^{\infty} \left( \frac{a_n}{a_{n+1}} - 1 \right) ∑ n = 1 ∞ ( a n + 1 a n − 1 )
收敛。
解答题 18 设
B B B
是秩为
2 2 2
的
5 × 4 5 \times 4 5 × 4
矩阵,
α 1 = ( 1 , 1 , 2 , 3 ) T , α 2 = ( − 1 , 1 , 4 , − 1 ) T , α 3 = ( 5 , − 1 , − 8 , 9 ) T \alpha_1 = (1,1,2,3)^T,\alpha_2 = (- 1,1,4, - 1)^T,\alpha_3 = (5, - 1, - 8,9)^T α 1 = ( 1 , 1 , 2 , 3 ) T , α 2 = ( − 1 , 1 , 4 , − 1 ) T , α 3 = ( 5 , − 1 , − 8 , 9 ) T 是齐次线性方程组
B x = 0 Bx = 0 B x = 0
的解向量,求
B x = 0 Bx = 0 B x = 0
的解空间的一个标准正交基.
【答案】
解空间的一个标准正交基为:
e 1 = 1 15 ( 1 1 2 3 ) , e 2 = 1 39 ( − 2 1 5 − 3 ) \mathbf{e}_1 = \frac{1}{\sqrt{15}} \begin{pmatrix} 1 \\ 1 \\ 2 \\ 3 \end{pmatrix}, \quad \mathbf{e}_2 = \frac{1}{\sqrt{39}} \begin{pmatrix} -2 \\ 1 \\ 5 \\ -3 \end{pmatrix} e 1 = 15 1 1 1 2 3 , e 2 = 39 1 − 2 1 5 − 3 【解析】
已知
B B B
是秩为
2 2 2
的
5 × 4 5 \times 4 5 × 4
矩阵,根据秩-零化度定理,解空间(零空间)的维数为
4 − 2 = 2 4 - 2 = 2 4 − 2 = 2
。给定解向量
α 1 , α 2 , α 3 \alpha_1, \alpha_2, \alpha_3 α 1 , α 2 , α 3
,通过线性相关性检验发现
α 3 = 2 α 1 − 3 α 2 \alpha_3 = 2\alpha_1 - 3\alpha_2 α 3 = 2 α 1 − 3 α 2
,因此
α 1 \alpha_1 α 1
和
α 2 \alpha_2 α 2
线性无关,构成解空间的一组基。
使用 Gram-Schmidt 正交化过程:
令
v 1 = α 1 = ( 1 1 2 3 ) \mathbf{v}_1 = \alpha_1 = \begin{pmatrix} 1 \\ 1 \\ 2 \\ 3 \end{pmatrix} v 1 = α 1 = 1 1 2 3
。 计算
⟨ α 2 , v 1 ⟩ = 5 \langle \alpha_2, \mathbf{v}_1 \rangle = 5 ⟨ α 2 , v 1 ⟩ = 5
和
⟨ v 1 , v 1 ⟩ = 15 \langle \mathbf{v}_1, \mathbf{v}_1 \rangle = 15 ⟨ v 1 , v 1 ⟩ = 15
,则
v 2 = α 2 − 5 15 v 1 = ( − 1 1 4 − 1 ) − 1 3 ( 1 1 2 3 ) = ( − 4 3 2 3 10 3 − 2 ) \mathbf{v}_2 = \alpha_2 - \frac{5}{15} \mathbf{v}_1 = \begin{pmatrix} -1 \\ 1 \\ 4 \\ -1 \end{pmatrix} - \frac{1}{3} \begin{pmatrix} 1 \\ 1 \\ 2 \\ 3 \end{pmatrix} = \begin{pmatrix} -\frac{4}{3} \\ \frac{2}{3} \\ \frac{10}{3} \\ -2 \end{pmatrix} v 2 = α 2 − 15 5 v 1 = − 1 1 4 − 1 − 3 1 1 1 2 3 = − 3 4 3 2 3 10 − 2
。 单位化:
∥ v 1 ∥ = 15 \|\mathbf{v}_1\| = \sqrt{15} ∥ v 1 ∥ = 15
,所以
e 1 = v 1 ∥ v 1 ∥ = 1 15 ( 1 1 2 3 ) \mathbf{e}_1 = \frac{\mathbf{v}_1}{\|\mathbf{v}_1\|} = \frac{1}{\sqrt{15}} \begin{pmatrix} 1 \\ 1 \\ 2 \\ 3 \end{pmatrix} e 1 = ∥ v 1 ∥ v 1 = 15 1 1 1 2 3
。∥ v 2 ∥ = 52 3 = 2 39 3 \|\mathbf{v}_2\| = \sqrt{\frac{52}{3}} = \frac{2\sqrt{39}}{3} ∥ v 2 ∥ = 3 52 = 3 2 39
,所以
e 2 = v 2 ∥ v 2 ∥ = 1 39 ( − 2 1 5 − 3 ) \mathbf{e}_2 = \frac{\mathbf{v}_2}{\|\mathbf{v}_2\|} = \frac{1}{\sqrt{39}} \begin{pmatrix} -2 \\ 1 \\ 5 \\ -3 \end{pmatrix} e 2 = ∥ v 2 ∥ v 2 = 39 1 − 2 1 5 − 3
.验证内积
⟨ e 1 , e 2 ⟩ = 0 \langle \mathbf{e}_1, \mathbf{e}_2 \rangle = 0 ⟨ e 1 , e 2 ⟩ = 0
,故
e 1 \mathbf{e}_1 e 1
和
e 2 \mathbf{e}_2 e 2
标准正交。
19 已知
ξ = ( 1 1 − 1 ) \xi = \begin{pmatrix}
1 \\
1 \\
-1
\end{pmatrix} ξ = 1 1 − 1
是矩阵
A = ( 2 − 1 2 5 a 3 − 1 b − 2 ) A = \begin{pmatrix}
2 & -1 & 2 \\
5 & a & 3 \\
-1 & b & -2
\end{pmatrix} A = 2 5 − 1 − 1 a b 2 3 − 2
的一个特征向量.
(1) 试确定参数
a , b a,b a , b
及特征向量
ξ \xi ξ
所对应的特征值;
(2) 问
A A A
能否相似于对角阵?说明理由.
【答案】
(1)
a = − 3 a = -3 a = − 3
,
b = 0 b = 0 b = 0
,特征值
λ = − 1 \lambda = -1 λ = − 1
。
(2)
A A A
不能相似于对角阵,因为特征值
λ = − 1 \lambda = -1 λ = − 1
的代数重数为 3,但几何重数为 1,几何重数小于代数重数。
【解析】
(1) 由于
ξ \xi ξ
是
A A A
的特征向量,满足
A ξ = λ ξ A \xi = \lambda \xi A ξ = λ ξ
。计算
A ξ A \xi A ξ
:
A ξ = ( 2 − 1 2 5 a 3 − 1 b − 2 ) ( 1 1 − 1 ) = ( 2 ⋅ 1 + ( − 1 ) ⋅ 1 + 2 ⋅ ( − 1 ) 5 ⋅ 1 + a ⋅ 1 + 3 ⋅ ( − 1 ) − 1 ⋅ 1 + b ⋅ 1 + ( − 2 ) ⋅ ( − 1 ) ) = ( − 1 2 + a 1 + b ) A \xi = \begin{pmatrix} 2 & -1 & 2 \\ 5 & a & 3 \\ -1 & b & -2 \end{pmatrix} \begin{pmatrix} 1 \\ 1 \\ -1 \end{pmatrix} = \begin{pmatrix} 2 \cdot 1 + (-1) \cdot 1 + 2 \cdot (-1) \\ 5 \cdot 1 + a \cdot 1 + 3 \cdot (-1) \\ -1 \cdot 1 + b \cdot 1 + (-2) \cdot (-1) \end{pmatrix} = \begin{pmatrix} -1 \\ 2 + a \\ 1 + b \end{pmatrix} A ξ = 2 5 − 1 − 1 a b 2 3 − 2 1 1 − 1 = 2 ⋅ 1 + ( − 1 ) ⋅ 1 + 2 ⋅ ( − 1 ) 5 ⋅ 1 + a ⋅ 1 + 3 ⋅ ( − 1 ) − 1 ⋅ 1 + b ⋅ 1 + ( − 2 ) ⋅ ( − 1 ) = − 1 2 + a 1 + b 令其等于
λ ξ = λ ( 1 1 − 1 ) = ( λ λ − λ ) \lambda \xi = \lambda \begin{pmatrix} 1 \\ 1 \\ -1 \end{pmatrix} = \begin{pmatrix} \lambda \\ \lambda \\ -\lambda \end{pmatrix} λ ξ = λ 1 1 − 1 = λ λ − λ
,得方程组:
{ − 1 = λ 2 + a = λ 1 + b = − λ \begin{cases} -1 = \lambda \\
2 + a = \lambda \\
1 + b = -\lambda
\end{cases} ⎩ ⎨ ⎧ − 1 = λ 2 + a = λ 1 + b = − λ 解得
λ = − 1 \lambda = -1 λ = − 1
,代入第二式得
2 + a = − 1 2 + a = -1 2 + a = − 1
,即
a = − 3 a = -3 a = − 3
;代入第三式得
1 + b = 1 1 + b = 1 1 + b = 1
,即
b = 0 b = 0 b = 0
。
(2) 代入
a = − 3 a = -3 a = − 3
和
b = 0 b = 0 b = 0
,得矩阵:
A = ( 2 − 1 2 5 − 3 3 − 1 0 − 2 ) A = \begin{pmatrix} 2 & -1 & 2 \\ 5 & -3 & 3 \\ -1 & 0 & -2 \end{pmatrix} A = 2 5 − 1 − 1 − 3 0 2 3 − 2 求特征多项式:
det ( A − λ I ) = det ( 2 − λ − 1 2 5 − 3 − λ 3 − 1 0 − 2 − λ ) \det(A - \lambda I) = \det \begin{pmatrix} 2-\lambda & -1 & 2 \\ 5 & -3-\lambda & 3 \\ -1 & 0 & -2-\lambda \end{pmatrix} det ( A − λ I ) = det 2 − λ 5 − 1 − 1 − 3 − λ 0 2 3 − 2 − λ 计算得
det ( A − λ I ) = − λ 3 − 3 λ 2 − 3 λ − 1 = − ( λ + 1 ) 3 \det(A - \lambda I) = -\lambda^3 - 3\lambda^2 - 3\lambda - 1 = -(\lambda + 1)^3 det ( A − λ I ) = − λ 3 − 3 λ 2 − 3 λ − 1 = − ( λ + 1 ) 3
,所以特征值为
λ = − 1 \lambda = -1 λ = − 1
(三重根),代数重数为 3。 计算几何重数,即解空间维数 of
A − ( − 1 ) I = A + I A - (-1)I = A + I A − ( − 1 ) I = A + I
:
A + I = ( 3 − 1 2 5 − 2 3 − 1 0 − 1 ) A + I = \begin{pmatrix} 3 & -1 & 2 \\ 5 & -2 & 3 \\ -1 & 0 & -1 \end{pmatrix} A + I = 3 5 − 1 − 1 − 2 0 2 3 − 1 行化简增广矩阵:
( 3 − 1 2 0 5 − 2 3 0 − 1 0 − 1 0 ) → ( 1 0 1 0 0 1 1 0 0 0 0 0 ) \begin{pmatrix} 3 & -1 & 2 & 0 \\ 5 & -2 & 3 & 0 \\ -1 & 0 & -1 & 0 \end{pmatrix} \rightarrow \begin{pmatrix} 1 & 0 & 1 & 0 \\ 0 & 1 & 1 & 0 \\ 0 & 0 & 0 & 0 \end{pmatrix} 3 5 − 1 − 1 − 2 0 2 3 − 1 0 0 0 → 1 0 0 0 1 0 1 1 0 0 0 0 得方程
x 1 + x 3 = 0 x_1 + x_3 = 0 x 1 + x 3 = 0
,
x 2 + x 3 = 0 x_2 + x_3 = 0 x 2 + x 3 = 0
,解向量为
x 3 ( − 1 − 1 1 ) x_3 \begin{pmatrix} -1 \\ -1 \\ 1 \end{pmatrix} x 3 − 1 − 1 1
,几何重数为 1。 由于几何重数小于代数重数,
A A A
不能相似于对角阵。
20 设
A A A
是
n n n
阶可逆方阵,将
A A A
的第
i i i
行和第
j j j
行对换后得到的矩阵记为
B B B
.
(1) 证明
B B B
可逆;
(2) 求
A B − 1 AB^{-1} A B − 1
.
【答案】 (1)
B B B
可逆。 (2)
A B − 1 = E AB^{-1} = E A B − 1 = E
,其中
E E E
是对换第
i i i
行和第
j j j
行的初等矩阵。
【解析】 (1) 由于
A A A
可逆,且
B B B
是通过对换
A A A
的第
i i i
行和第
j j j
行得到的矩阵,这一操作等价于左乘一个对换两行的初等矩阵
E E E
,即
B = E A B = EA B = E A
。初等矩阵
E E E
可逆,且
E − 1 = E E^{-1} = E E − 1 = E
。因此
B B B
是可逆矩阵的乘积,故
B B B
可逆。 (2) 由
B = E A B = EA B = E A
可得
B − 1 = A − 1 E − 1 = A − 1 E B^{-1} = A^{-1}E^{-1} = A^{-1}E B − 1 = A − 1 E − 1 = A − 1 E
。于是
A B − 1 = A ( A − 1 E ) = ( A A − 1 ) E = I E = E AB^{-1} = A(A^{-1}E) = (AA^{-1})E = IE = E A B − 1 = A ( A − 1 E ) = ( A A − 1 ) E = I E = E
,即
A B − 1 AB^{-1} A B − 1
等于对换第
i i i
行和第
j j j
行的初等矩阵
E E E
。
21 从学校乘汽车到火车站的途中有
3 3 3
个交通岗,假设在各个交通岗遇到红灯的事件是相互独立的,
并且概率都是
2 5 \frac{2}{5} 5 2
.设
X X X
为途中遇到红灯的次数,求随机变量
X X X
的分布律、分布函数和数学期望.
【答案】 随机变量
X X X
的分布律为:
P ( X = 0 ) = 27 125 , P ( X = 1 ) = 54 125 , P ( X = 2 ) = 36 125 , P ( X = 3 ) = 8 125 P(X=0) = \frac{27}{125}, \quad P(X=1) = \frac{54}{125}, \quad P(X=2) = \frac{36}{125}, \quad P(X=3) = \frac{8}{125} P ( X = 0 ) = 125 27 , P ( X = 1 ) = 125 54 , P ( X = 2 ) = 125 36 , P ( X = 3 ) = 125 8 分布函数为:
F ( x ) = { 0 x < 0 27 125 0 ≤ x < 1 81 125 1 ≤ x < 2 117 125 2 ≤ x < 3 1 x ≥ 3 F(x) =
\begin{cases}
0 & x < 0 \\
\frac{27}{125} & 0 \leq x < 1 \\
\frac{81}{125} & 1 \leq x < 2 \\
\frac{117}{125} & 2 \leq x < 3 \\
1 & x \geq 3
\end{cases} F ( x ) = ⎩ ⎨ ⎧ 0 125 27 125 81 125 117 1 x < 0 0 ≤ x < 1 1 ≤ x < 2 2 ≤ x < 3 x ≥ 3 数学期望为:
E [ X ] = 6 5 E[X] = \frac{6}{5} E [ X ] = 5 6 【解析】 由于有 3 个交通岗,每个交通岗遇到红灯的事件相互独立,且概率均为
2 5 \frac{2}{5} 5 2
,因此
X X X
服从二项分布
B ( 3 , 2 5 ) B(3, \frac{2}{5}) B ( 3 , 5 2 )
。 分布律由二项分布公式
P ( X = k ) = ( 3 k ) ( 2 5 ) k ( 3 5 ) 3 − k P(X = k) = \binom{3}{k} \left(\frac{2}{5}\right)^k \left(\frac{3}{5}\right)^{3-k} P ( X = k ) = ( k 3 ) ( 5 2 ) k ( 5 3 ) 3 − k
计算可得:
P ( X = 0 ) = ( 3 0 ) ( 2 5 ) 0 ( 3 5 ) 3 = 27 125 P(X=0) = \binom{3}{0} \left(\frac{2}{5}\right)^0 \left(\frac{3}{5}\right)^3 = \frac{27}{125} P ( X = 0 ) = ( 0 3 ) ( 5 2 ) 0 ( 5 3 ) 3 = 125 27 P ( X = 1 ) = ( 3 1 ) ( 2 5 ) 1 ( 3 5 ) 2 = 54 125 P(X=1) = \binom{3}{1} \left(\frac{2}{5}\right)^1 \left(\frac{3}{5}\right)^2 = \frac{54}{125} P ( X = 1 ) = ( 1 3 ) ( 5 2 ) 1 ( 5 3 ) 2 = 125 54 P ( X = 2 ) = ( 3 2 ) ( 2 5 ) 2 ( 3 5 ) 1 = 36 125 P(X=2) = \binom{3}{2} \left(\frac{2}{5}\right)^2 \left(\frac{3}{5}\right)^1 = \frac{36}{125} P ( X = 2 ) = ( 2 3 ) ( 5 2 ) 2 ( 5 3 ) 1 = 125 36 P ( X = 3 ) = ( 3 3 ) ( 2 5 ) 3 ( 3 5 ) 0 = 8 125 P(X=3) = \binom{3}{3} \left(\frac{2}{5}\right)^3 \left(\frac{3}{5}\right)^0 = \frac{8}{125} P ( X = 3 ) = ( 3 3 ) ( 5 2 ) 3 ( 5 3 ) 0 = 125 8 分布函数
F ( x ) = P ( X ≤ x ) F(x) = P(X \leq x) F ( x ) = P ( X ≤ x )
是累积概率,根据
x x x
的取值范围分段定义:当
x < 0 x < 0 x < 0
时,
F ( x ) = 0 F(x) = 0 F ( x ) = 0 当
0 ≤ x < 1 0 \leq x < 1 0 ≤ x < 1
时,
F ( x ) = P ( X = 0 ) = 27 125 F(x) = P(X=0) = \frac{27}{125} F ( x ) = P ( X = 0 ) = 125 27 当
1 ≤ x < 2 1 \leq x < 2 1 ≤ x < 2
时,
F ( x ) = P ( X = 0 ) + P ( X = 1 ) = 81 125 F(x) = P(X=0) + P(X=1) = \frac{81}{125} F ( x ) = P ( X = 0 ) + P ( X = 1 ) = 125 81 当
2 ≤ x < 3 2 \leq x < 3 2 ≤ x < 3
时,
F ( x ) = P ( X = 0 ) + P ( X = 1 ) + P ( X = 2 ) = 117 125 F(x) = P(X=0) + P(X=1) + P(X=2) = \frac{117}{125} F ( x ) = P ( X = 0 ) + P ( X = 1 ) + P ( X = 2 ) = 125 117 当
x ≥ 3 x \geq 3 x ≥ 3
时,
F ( x ) = 1 F(x) = 1 F ( x ) = 1 数学期望对于二项分布有
E [ X ] = n p = 3 × 2 5 = 6 5 E[X] = np = 3 \times \frac{2}{5} = \frac{6}{5} E [ X ] = n p = 3 × 5 2 = 5 6
,也可直接计算:E [ X ] = ∑ k = 0 3 k P ( X = k ) = 0 × 27 125 + 1 × 54 125 + 2 × 36 125 + 3 × 8 125 = 54 125 + 72 125 + 24 125 = 150 125 = 6 5 E[X] = \sum_{k=0}^{3} k P(X=k) = 0 \times \frac{27}{125} + 1 \times \frac{54}{125} + 2 \times \frac{36}{125} + 3 \times \frac{8}{125} = \frac{54}{125} + \frac{72}{125} + \frac{24}{125} = \frac{150}{125} = \frac{6}{5} E [ X ] = ∑ k = 0 3 k P ( X = k ) = 0 × 125 27 + 1 × 125 54 + 2 × 125 36 + 3 × 125 8 = 125 54 + 125 72 + 125 24 = 125 150 = 5 6 22 设总体
X X X
的概率密度为
f ( x ) = { ( θ + 1 ) x θ , 0 < x < 1 , 0 , 其它 , f(x) = \begin{cases}
(\theta + 1)x^{\theta}, & 0 < x < 1, \\
0, & \text{其它}, \\
\end{cases} f ( x ) = { ( θ + 1 ) x θ , 0 , 0 < x < 1 , 其它 , 其中
θ > − 1 \theta > - 1 θ > − 1
是未知参数.
x 1 , x 2 , ⋯ , x n x_1,x_2, \cdots ,x_n x 1 , x 2 , ⋯ , x n
是来自总体
X X X
的一个容量为
n n n
的简单随机样本,
分别用矩估计法和最大似然估计法求
θ \theta θ
的估计量.
【答案】
矩估计法得到的估计量为:
θ ^ M = 2 x ˉ − 1 1 − x ˉ \hat{\theta}_M = \frac{2\bar{x} - 1}{1 - \bar{x}} θ ^ M = 1 − x ˉ 2 x ˉ − 1 其中
x ˉ = 1 n ∑ i = 1 n x i \bar{x} = \frac{1}{n} \sum_{i=1}^n x_i x ˉ = n 1 ∑ i = 1 n x i
。
最大似然估计法得到的估计量为:
θ ^ M L E = − 1 − n ∑ i = 1 n ln x i \hat{\theta}_{MLE} = -1 - \frac{n}{\sum_{i=1}^n \ln x_i} θ ^ M L E = − 1 − ∑ i = 1 n ln x i n 【解析】
对于矩估计法,首先计算总体均值
E [ X ] E[X] E [ X ]
。由于概率密度函数为
f ( x ) = ( θ + 1 ) x θ f(x) = (\theta + 1)x^\theta f ( x ) = ( θ + 1 ) x θ
在区间
( 0 , 1 ) (0,1) ( 0 , 1 )
上,有:
E [ X ] = ∫ 0 1 x ⋅ ( θ + 1 ) x θ d x = ( θ + 1 ) ∫ 0 1 x θ + 1 d x = ( θ + 1 ) [ x θ + 2 θ + 2 ] 0 1 = θ + 1 θ + 2 E[X] = \int_0^1 x \cdot (\theta + 1) x^\theta \, dx = (\theta + 1) \int_0^1 x^{\theta + 1} \, dx = (\theta + 1) \left[ \frac{x^{\theta + 2}}{\theta + 2} \right]_0^1 = \frac{\theta + 1}{\theta + 2} E [ X ] = ∫ 0 1 x ⋅ ( θ + 1 ) x θ d x = ( θ + 1 ) ∫ 0 1 x θ + 1 d x = ( θ + 1 ) [ θ + 2 x θ + 2 ] 0 1 = θ + 2 θ + 1 设总体均值等于样本均值
x ˉ \bar{x} x ˉ
,即:
θ + 1 θ + 2 = x ˉ \frac{\theta + 1}{\theta + 2} = \bar{x} θ + 2 θ + 1 = x ˉ 解此方程求
θ \theta θ
:
θ + 1 = x ˉ ( θ + 2 ) \theta + 1 = \bar{x} (\theta + 2) θ + 1 = x ˉ ( θ + 2 )
θ + 1 = x ˉ θ + 2 x ˉ \theta + 1 = \bar{x} \theta + 2\bar{x} θ + 1 = x ˉ θ + 2 x ˉ
θ − x ˉ θ = 2 x ˉ − 1 \theta - \bar{x} \theta = 2\bar{x} - 1 θ − x ˉ θ = 2 x ˉ − 1
θ ( 1 − x ˉ ) = 2 x ˉ − 1 \theta (1 - \bar{x}) = 2\bar{x} - 1 θ ( 1 − x ˉ ) = 2 x ˉ − 1
θ = 2 x ˉ − 1 1 − x ˉ \theta = \frac{2\bar{x} - 1}{1 - \bar{x}} θ = 1 − x ˉ 2 x ˉ − 1 因此,矩估计量为
θ ^ M = 2 x ˉ − 1 1 − x ˉ \hat{\theta}_M = \frac{2\bar{x} - 1}{1 - \bar{x}} θ ^ M = 1 − x ˉ 2 x ˉ − 1
。
对于最大似然估计法,似然函数为:
L ( θ ) = ∏ i = 1 n f ( x i ) = ∏ i = 1 n ( θ + 1 ) x i θ = ( θ + 1 ) n ∏ i = 1 n x i θ L(\theta) = \prod_{i=1}^n f(x_i) = \prod_{i=1}^n (\theta + 1) x_i^\theta = (\theta + 1)^n \prod_{i=1}^n x_i^\theta L ( θ ) = i = 1 ∏ n f ( x i ) = i = 1 ∏ n ( θ + 1 ) x i θ = ( θ + 1 ) n i = 1 ∏ n x i θ 取对数似然函数:
l ( θ ) = ln L ( θ ) = n ln ( θ + 1 ) + θ ∑ i = 1 n ln x i l(\theta) = \ln L(\theta) = n \ln(\theta + 1) + \theta \sum_{i=1}^n \ln x_i l ( θ ) = ln L ( θ ) = n ln ( θ + 1 ) + θ i = 1 ∑ n ln x i 对
θ \theta θ
求导并令导数为零:
∂ l ∂ θ = n θ + 1 + ∑ i = 1 n ln x i = 0 \frac{\partial l}{\partial \theta} = \frac{n}{\theta + 1} + \sum_{i=1}^n \ln x_i = 0 ∂ θ ∂ l = θ + 1 n + i = 1 ∑ n ln x i = 0 解得:
n θ + 1 = − ∑ i = 1 n ln x i \frac{n}{\theta + 1} = -\sum_{i=1}^n \ln x_i θ + 1 n = − i = 1 ∑ n ln x i
θ + 1 = − n ∑ i = 1 n ln x i \theta + 1 = -\frac{n}{\sum_{i=1}^n \ln x_i} θ + 1 = − ∑ i = 1 n ln x i n
θ = − 1 − n ∑ i = 1 n ln x i \theta = -1 - \frac{n}{\sum_{i=1}^n \ln x_i} θ = − 1 − ∑ i = 1 n ln x i n 二阶导数为
∂ 2 l ∂ θ 2 = − n ( θ + 1 ) 2 < 0 \frac{\partial^2 l}{\partial \theta^2} = -\frac{n}{(\theta + 1)^2} < 0 ∂ θ 2 ∂ 2 l = − ( θ + 1 ) 2 n < 0
,故为最大值。因此,最大似然估计量为
θ ^ M L E = − 1 − n ∑ i = 1 n ln x i \hat{\theta}_{MLE} = -1 - \frac{n}{\sum_{i=1}^n \ln x_i} θ ^ M L E = − 1 − ∑ i = 1 n l n x i n
。