卷 3 填空题 1~6小题,每小题4分,共24分
1 lim n → ∞ ( n + 1 n ) ( − 1 ) n = \lim_{n \to \infty} \left(\frac{n + 1}{n} \right)^{(- 1)^n} = lim n → ∞ ( n n + 1 ) ( − 1 ) n =
______.
【答案】
1 1 1
【解析】 考虑极限
lim n → ∞ ( n + 1 n ) ( − 1 ) n \lim_{n \to \infty} \left(\frac{n + 1}{n} \right)^{(-1)^n} lim n → ∞ ( n n + 1 ) ( − 1 ) n
。 首先,简化底数:
n + 1 n = 1 + 1 n \frac{n+1}{n} = 1 + \frac{1}{n} n n + 1 = 1 + n 1
,因此表达式化为
( 1 + 1 n ) ( − 1 ) n \left(1 + \frac{1}{n}\right)^{(-1)^n} ( 1 + n 1 ) ( − 1 ) n
。 指数
( − 1 ) n (-1)^n ( − 1 ) n
在
n n n
为偶数时取值为 1,在
n n n
为奇数时取值为 -1。
当
n n n
为偶数时,
( − 1 ) n = 1 (-1)^n = 1 ( − 1 ) n = 1
,表达式为
( 1 + 1 n ) 1 = 1 + 1 n \left(1 + \frac{1}{n}\right)^1 = 1 + \frac{1}{n} ( 1 + n 1 ) 1 = 1 + n 1
,当
n → ∞ n \to \infty n → ∞
时,
1 n → 0 \frac{1}{n} \to 0 n 1 → 0
,故极限为 1。 当
n n n
为奇数时,
( − 1 ) n = − 1 (-1)^n = -1 ( − 1 ) n = − 1
,表达式为
( 1 + 1 n ) − 1 = 1 1 + 1 n = n n + 1 \left(1 + \frac{1}{n}\right)^{-1} = \frac{1}{1 + \frac{1}{n}} = \frac{n}{n+1} ( 1 + n 1 ) − 1 = 1 + n 1 1 = n + 1 n
,当
n → ∞ n \to \infty n → ∞
时,
n n + 1 → 1 \frac{n}{n+1} \to 1 n + 1 n → 1
,故极限为 1。 由于在
n n n
为偶数和奇数时极限均为 1,因此整体极限为 1。
2 设函数
f ( x ) f(x) f ( x )
在
x = 2 x = 2 x = 2
的某邻域内可导,且
f ′ ( x ) = e f ( x ) f'(x) = \e^{f(x)} f ′ ( x ) = e f ( x )
,
f ( 2 ) = 1 f(2) = 1 f ( 2 ) = 1
,则
f ′ ′ ′ ( 2 ) = f'''(2) = f ′′′ ( 2 ) =
______.
【答案】
2 e 3 2e^3 2 e 3
【解析】 已知函数
f ( x ) f(x) f ( x )
在
x = 2 x = 2 x = 2
的某邻域内可导,且
f ′ ( x ) = e f ( x ) f'(x) = e^{f(x)} f ′ ( x ) = e f ( x )
,
f ( 2 ) = 1 f(2) = 1 f ( 2 ) = 1
。 首先,求二阶导数:
f ′ ′ ( x ) = d d x [ f ′ ( x ) ] = d d x [ e f ( x ) ] = e f ( x ) ⋅ f ′ ( x ) = e f ( x ) ⋅ e f ( x ) = e 2 f ( x ) f''(x) = \frac{d}{dx} [f'(x)] = \frac{d}{dx} [e^{f(x)}] = e^{f(x)} \cdot f'(x) = e^{f(x)} \cdot e^{f(x)} = e^{2f(x)} f ′′ ( x ) = d x d [ f ′ ( x )] = d x d [ e f ( x ) ] = e f ( x ) ⋅ f ′ ( x ) = e f ( x ) ⋅ e f ( x ) = e 2 f ( x ) 接着,求三阶导数:
f ′ ′ ′ ( x ) = d d x [ f ′ ′ ( x ) ] = d d x [ e 2 f ( x ) ] = e 2 f ( x ) ⋅ 2 f ′ ( x ) = 2 e 2 f ( x ) ⋅ e f ( x ) = 2 e 3 f ( x ) f'''(x) = \frac{d}{dx} [f''(x)] = \frac{d}{dx} [e^{2f(x)}] = e^{2f(x)} \cdot 2 f'(x) = 2 e^{2f(x)} \cdot e^{f(x)} = 2 e^{3f(x)} f ′′′ ( x ) = d x d [ f ′′ ( x )] = d x d [ e 2 f ( x ) ] = e 2 f ( x ) ⋅ 2 f ′ ( x ) = 2 e 2 f ( x ) ⋅ e f ( x ) = 2 e 3 f ( x ) 代入
x = 2 x = 2 x = 2
和
f ( 2 ) = 1 f(2) = 1 f ( 2 ) = 1
:
f ′ ′ ′ ( 2 ) = 2 e 3 f ( 2 ) = 2 e 3 ⋅ 1 = 2 e 3 f'''(2) = 2 e^{3f(2)} = 2 e^{3 \cdot 1} = 2 e^3 f ′′′ ( 2 ) = 2 e 3 f ( 2 ) = 2 e 3 ⋅ 1 = 2 e 3 因此,
f ′ ′ ′ ( 2 ) = 2 e 3 f'''(2) = 2e^3 f ′′′ ( 2 ) = 2 e 3
。
3 设函数
f ( u ) f(u) f ( u )
可微,且
f ′ ( 0 ) = 1 2 f'(0) = \frac{1}{2} f ′ ( 0 ) = 2 1
,
则
z = f ( 4 x 2 − y 2 ) z = f\left(4x^2 - y^2 \right) z = f ( 4 x 2 − y 2 )
在点
( 1 , 2 ) (1,2) ( 1 , 2 )
处的全微分
d z ∣ ( 1 , 2 ) = \dz\big|_{\left(1,2 \right)} = d z ( 1 , 2 ) =
______.
【答案】
4 d x − 2 d y 4 \, dx - 2 \, dy 4 d x − 2 d y
【解析】
函数
z = f ( 4 x 2 − y 2 ) z = f(4x^2 - y^2) z = f ( 4 x 2 − y 2 )
在点
( 1 , 2 ) (1,2) ( 1 , 2 )
处的全微分表示为
d z = ∂ z ∂ x d x + ∂ z ∂ y d y .
\mathrm{d}z = \frac{\partial z}{\partial x} \mathrm{d}x + \frac{\partial z}{\partial y} \mathrm{d}y .
d z = ∂ x ∂ z d x + ∂ y ∂ z d y . 首先,计算中间变量
u = 4 x 2 − y 2 u = 4x^2 - y^2 u = 4 x 2 − y 2
在点
( 1 , 2 ) (1,2) ( 1 , 2 )
处的值:
u = 4 ( 1 ) 2 − ( 2 ) 2 = 4 − 4 = 0.
u = 4(1)^2 - (2)^2 = 4 - 4 = 0 .
u = 4 ( 1 ) 2 − ( 2 ) 2 = 4 − 4 = 0. 已知
f ′ ( 0 ) = 1 2 f'(0) = \dfrac{1}{2} f ′ ( 0 ) = 2 1
。
使用链式法则求偏导数:
∂ z ∂ x = f ′ ( u ) ⋅ ∂ u ∂ x = f ′ ( u ) ⋅ 8 x ,
\frac{\partial z}{\partial x} = f'(u) \cdot \frac{\partial u}{\partial x} = f'(u) \cdot 8x ,
∂ x ∂ z = f ′ ( u ) ⋅ ∂ x ∂ u = f ′ ( u ) ⋅ 8 x , 在点
( 1 , 2 ) (1,2) ( 1 , 2 )
处,
∂ z ∂ x = f ′ ( 0 ) ⋅ 8 ⋅ 1 = 1 2 ⋅ 8 = 4.
\frac{\partial z}{\partial x} = f'(0) \cdot 8 \cdot 1 = \frac{1}{2} \cdot 8 = 4 .
∂ x ∂ z = f ′ ( 0 ) ⋅ 8 ⋅ 1 = 2 1 ⋅ 8 = 4. ∂ z ∂ y = f ′ ( u ) ⋅ ∂ u ∂ y = f ′ ( u ) ⋅ ( − 2 y ) ,
\frac{\partial z}{\partial y} = f'(u) \cdot \frac{\partial u}{\partial y} = f'(u) \cdot (-2y) ,
∂ y ∂ z = f ′ ( u ) ⋅ ∂ y ∂ u = f ′ ( u ) ⋅ ( − 2 y ) , 在点
( 1 , 2 ) (1,2) ( 1 , 2 )
处,
∂ z ∂ y = f ′ ( 0 ) ⋅ ( − 2 ⋅ 2 ) = 1 2 ⋅ ( − 4 ) = − 2.
\frac{\partial z}{\partial y} = f'(0) \cdot (-2 \cdot 2) = \frac{1}{2} \cdot (-4) = -2 .
∂ y ∂ z = f ′ ( 0 ) ⋅ ( − 2 ⋅ 2 ) = 2 1 ⋅ ( − 4 ) = − 2. 因此,全微分为
d z = 4 d x − 2 d y .
\mathrm{d}z = 4 \, \mathrm{d}x - 2 \, \mathrm{d}y .
d z = 4 d x − 2 d y . 4 同试卷 1 第 5 题
5 同试卷 1 第 6 题
6 设总体
X X X
的概率密度为
f ( x ) = 1 2 e − ∣ x ∣ f(x) = \frac{1}{2}\e^{- |x|} f ( x ) = 2 1 e − ∣ x ∣
(
− ∞ < x < + ∞ -\infty < x < +\infty − ∞ < x < + ∞
),
x 1 , x 2 , ⋯ , x n x_1,x_2, \cdots ,x_n x 1 , x 2 , ⋯ , x n
为总体
X X X
的简单随机样本,其样本方差
S 2 S^2 S 2
,则
E S 2 = ES^2 = E S 2 =
______.
【答案】 2
【解析】 因为样本方差是总体方差的无偏估计量,所以
E ( S 2 ) = D ( X ) = E ( X 2 ) − [ E ( X ) ] 2 = ∫ − ∞ + ∞ x 2 f ( x ) d x − [ ∫ − ∞ + ∞ x f ( x ) d x ] 2 = 2 ∫ 0 + ∞ x 2 f ( x ) d x − 0 = − ∫ 0 + ∞ x 2 d ( e − x ) = [ − x 2 e − x ] 0 + ∞ + ∫ 0 + ∞ e − x d ( x 2 ) = 0 − 2 ∫ 0 ∞ x d ( e − x ) = [ − 2 x e − x ] 0 + ∞ + 2 ∫ 0 + ∞ e − x d x = 0 + 2 = 2.
\begin{aligned}
E(S^2) &= D(X) = E(X^2) - [E(X)]^2 = \int_{-\infty}^{+\infty} x^2 f(x)\,dx - \left[\int_{-\infty}^{+\infty} x f(x)\,dx\right]^2 \\
&= 2\int_0^{+\infty} x^2 f(x)\,dx - 0 = -\int_0^{+\infty} x^2\,\mathrm{d}(e^{-x}) = \left[-x^2 e^{-x}\right]_0^{+\infty} + \int_0^{+\infty} e^{-x}\,\mathrm{d}(x^2) \\
&= 0 - 2\int_0^{\infty} x\,\mathrm{d}(e^{-x}) = \left[-2x e^{-x}\right]_0^{+\infty} + 2\int_0^{+\infty} e^{-x}\,\mathrm{d}x = 0 + 2 = 2.
\end{aligned}
E ( S 2 ) = D ( X ) = E ( X 2 ) − [ E ( X ) ] 2 = ∫ − ∞ + ∞ x 2 f ( x ) d x − [ ∫ − ∞ + ∞ x f ( x ) d x ] 2 = 2 ∫ 0 + ∞ x 2 f ( x ) d x − 0 = − ∫ 0 + ∞ x 2 d ( e − x ) = [ − x 2 e − x ] 0 + ∞ + ∫ 0 + ∞ e − x d ( x 2 ) = 0 − 2 ∫ 0 ∞ x d ( e − x ) = [ − 2 x e − x ] 0 + ∞ + 2 ∫ 0 + ∞ e − x d x = 0 + 2 = 2. 选择题 7~14小题,每小题4分,共32分
7 同试卷 1 第 7 题
8 设函数
f ( x ) f(x) f ( x )
在
x = 0 x = 0 x = 0
处连续,且
lim h → 0 f ( h 2 ) h 2 = 1 \lim_{h \to 0}\frac{f\left(h^2\right)}{h^2} = 1 lim h → 0 h 2 f ( h 2 ) = 1
,则
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正确答案:C 【解析】 令
x = h 2 x = h^2 x = h 2
,由题设可得
lim h → 0 f ( h 2 ) h 2 = lim x → 0 + f ( x ) x = 1.
\lim_{h \to 0} \frac{f(h^2)}{h^2} = \lim_{x \to 0^+} \frac{f(x)}{x} = 1.
h → 0 lim h 2 f ( h 2 ) = x → 0 + lim x f ( x ) = 1. 因为函数
f ( x ) f(x) f ( x )
在点
x = 0 x = 0 x = 0
处连续,所以
f ( 0 ) = lim x → 0 + f ( x ) = lim x → 0 + f ( x ) x ⋅ x = 1 ⋅ 0 = 0.
f(0) = \lim_{x \to 0^+} f(x) = \lim_{x \to 0^+} \frac{f(x)}{x} \cdot x = 1 \cdot 0 = 0.
f ( 0 ) = x → 0 + lim f ( x ) = x → 0 + lim x f ( x ) ⋅ x = 1 ⋅ 0 = 0. 由导数的定义有
1 = lim x → 0 + f ( x ) x = lim x → 0 + f ( x ) − f ( 0 ) x − 0 = f + ′ ( 0 ) ,
1 = \lim_{x \to 0^+} \frac{f(x)}{x} = \lim_{x \to 0^+} \frac{f(x) - f(0)}{x - 0} = f'_+(0),
1 = x → 0 + lim x f ( x ) = x → 0 + lim x − 0 f ( x ) − f ( 0 ) = f + ′ ( 0 ) , 即
f + ′ ( 0 ) f'_+(0) f + ′ ( 0 )
存在。
9 同试卷 1 第 9 题
10 设非齐次线性微分方程
y ′ + P ( x ) y = Q ( x ) y' + P(x)y = Q(x) y ′ + P ( x ) y = Q ( x )
有两个不同的解
y 1 ( x ) , y 2 ( x ) y_1(x),y_2(x) y 1 ( x ) , y 2 ( x )
,
C C C
为任意常数,
则该方程通解是
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正确答案:B 【解析】 对于非齐次线性微分方程y ′ + P ( x ) y = Q ( x ) y' + P(x)y = Q(x) y ′ + P ( x ) y = Q ( x )
, 若
y 1 ( x ) y_1(x) y 1 ( x )
和
y 2 ( x ) y_2(x) y 2 ( x )
是其两个不同的解,则它们的差y 1 ( x ) − y 2 ( x ) y_1(x) - y_2(x) y 1 ( x ) − y 2 ( x ) 是对应齐次方程y ′ + P ( x ) y = 0 y' + P(x)y = 0 y ′ + P ( x ) y = 0 的解。
由于
y 1 y_1 y 1
和
y 2 y_2 y 2
不同,
y 1 − y 2 y_1 - y_2 y 1 − y 2
非零,因此齐次方程的通解为C [ y 1 ( x ) − y 2 ( x ) ] C[y_1(x) - y_2(x)] C [ y 1 ( x ) − y 2 ( x )]
, 其中
C C C
为任意常数。
非齐次方程的通解由齐次方程的通解加上一个特解(如
y 1 ( x ) y_1(x) y 1 ( x )
或
y 2 ( x ) y_2(x) y 2 ( x )
)构成。因此,通解可表示为y 1 ( x ) + C [ y 1 ( x ) − y 2 ( x ) ] y_1(x) + C[y_1(x) - y_2(x)] y 1 ( x ) + C [ y 1 ( x ) − y 2 ( x )]
, 对应选项 B。
选项 A 仅为齐次通解,缺少特解;选项 C 和 D 中的
y 1 ( x ) + y 2 ( x ) y_1(x) + y_2(x) y 1 ( x ) + y 2 ( x )
不是齐次方程的解,因为代入原方程得
2 Q ( x ) 2Q(x) 2 Q ( x )
,除非
Q ( x ) = 0 Q(x)=0 Q ( x ) = 0
,否则不满足齐次方程。故 B 正确。
11 同试卷 1 第 10 题
12 同试卷 1 第 11 题
13 同试卷 1 第 12 题
14 同试卷 1 第 14 题
解答题 15~23小题,共94分
15 (本题满分 7 分)
设
f ( x , y ) = y 1 + x y − 1 − y sin π x y arctan x f(x,y) = \frac{y}{1 + xy} - \frac{1 - y\sin \frac{\pi x}{y}}{\arctan x} f ( x , y ) = 1 + x y y − a r c t a n x 1 − y s i n y π x
,
x > 0 , y > 0 x > 0,y > 0 x > 0 , y > 0
,求
(1)
g ( x ) = lim y → + ∞ f ( x , y ) g(x) = \lim_{y \to +\infty} f\left(x,y \right) g ( x ) = lim y → + ∞ f ( x , y )
;
(2)
lim x → 0 + g ( x ) \lim_{x \to 0^+} g(x) lim x → 0 + g ( x )
.
【答案】 (1)
g ( x ) = 1 x − 1 − π x arctan x g(x) = \frac{1}{x} - \frac{1 - \pi x}{\arctan x} g ( x ) = x 1 − a r c t a n x 1 − π x (2)
lim x → 0 + g ( x ) = π \lim_{x \to 0^+} g(x) = \pi lim x → 0 + g ( x ) = π
【解析】 (1) 求
g ( x ) = lim y → + ∞ f ( x , y ) g(x) = \lim_{y \to +\infty} f(x,y) g ( x ) = lim y → + ∞ f ( x , y )
。 首先,计算
f ( x , y ) = y 1 + x y − 1 − y sin π x y arctan x f(x,y) = \frac{y}{1 + xy} - \frac{1 - y \sin \frac{\pi x}{y}}{\arctan x} f ( x , y ) = 1 + x y y − a r c t a n x 1 − y s i n y π x
当
y → + ∞ y \to +\infty y → + ∞
时的极限。 对于第一项:
lim y → + ∞ y 1 + x y = lim y → + ∞ 1 1 y + x = 1 x \lim_{y \to +\infty} \frac{y}{1 + xy} = \lim_{y \to +\infty} \frac{1}{\frac{1}{y} + x} = \frac{1}{x} y → + ∞ lim 1 + x y y = y → + ∞ lim y 1 + x 1 = x 1 对于第二项: 令
t = π x y t = \frac{\pi x}{y} t = y π x
,则当
y → + ∞ y \to +\infty y → + ∞
时,
t → 0 t \to 0 t → 0
,有
lim y → + ∞ y sin π x y = lim t → 0 π x t sin t = π x ⋅ lim t → 0 sin t t = π x \lim_{y \to +\infty} y \sin \frac{\pi x}{y} = \lim_{t \to 0} \frac{\pi x}{t} \sin t = \pi x \cdot \lim_{t \to 0} \frac{\sin t}{t} = \pi x y → + ∞ lim y sin y π x = t → 0 lim t π x sin t = π x ⋅ t → 0 lim t sin t = π x 因此,
lim y → + ∞ ( 1 − y sin π x y ) = 1 − π x \lim_{y \to +\infty} \left( 1 - y \sin \frac{\pi x}{y} \right) = 1 - \pi x y → + ∞ lim ( 1 − y sin y π x ) = 1 − π x 由于
arctan x \arctan x arctan x
与
y y y
无关,第二项的极限为
lim y → + ∞ ( − 1 − y sin π x y arctan x ) = − 1 − π x arctan x \lim_{y \to +\infty} \left( - \frac{1 - y \sin \frac{\pi x}{y}}{\arctan x} \right) = - \frac{1 - \pi x}{\arctan x} y → + ∞ lim ( − arctan x 1 − y sin y π x ) = − arctan x 1 − π x 综上,
g ( x ) = 1 x − 1 − π x arctan x g(x) = \frac{1}{x} - \frac{1 - \pi x}{\arctan x} g ( x ) = x 1 − arctan x 1 − π x (2) 求
lim x → 0 + g ( x ) \lim_{x \to 0^+} g(x) lim x → 0 + g ( x )
。 由 (1) 得
g ( x ) = 1 x − 1 − π x arctan x g(x) = \frac{1}{x} - \frac{1 - \pi x}{\arctan x} g ( x ) = x 1 − arctan x 1 − π x 当
x → 0 + x \to 0^+ x → 0 +
时,此为
∞ − ∞ \infty - \infty ∞ − ∞
型未定式。将其通分:
g ( x ) = arctan x − x ( 1 − π x ) x arctan x = arctan x − x + π x 2 x arctan x g(x) = \frac{\arctan x - x (1 - \pi x)}{x \arctan x} = \frac{\arctan x - x + \pi x^2}{x \arctan x} g ( x ) = x arctan x arctan x − x ( 1 − π x ) = x arctan x arctan x − x + π x 2 当
x → 0 + x \to 0^+ x → 0 +
时,分子和分母均趋于 0,应用洛必达法则。 令
h ( x ) = arctan x − x + π x 2 h(x) = \arctan x - x + \pi x^2 h ( x ) = arctan x − x + π x 2
,
k ( x ) = x arctan x k(x) = x \arctan x k ( x ) = x arctan x
。 一阶导数:
h ′ ( x ) = 1 1 + x 2 − 1 + 2 π x h'(x) = \frac{1}{1+x^2} - 1 + 2\pi x h ′ ( x ) = 1 + x 2 1 − 1 + 2 π x
k ′ ( x ) = arctan x + x 1 + x 2 k'(x) = \arctan x + \frac{x}{1+x^2} k ′ ( x ) = arctan x + 1 + x 2 x 当
x → 0 + x \to 0^+ x → 0 +
,
h ′ ( 0 ) = 0 h'(0) = 0 h ′ ( 0 ) = 0
,
k ′ ( 0 ) = 0 k'(0) = 0 k ′ ( 0 ) = 0
,仍需洛必达法则。 二阶导数:
h ′ ′ ( x ) = − 2 x ( 1 + x 2 ) 2 + 2 π h''(x) = -\frac{2x}{(1+x^2)^2} + 2\pi h ′′ ( x ) = − ( 1 + x 2 ) 2 2 x + 2 π
k ′ ′ ( x ) = 1 1 + x 2 + 1 − x 2 ( 1 + x 2 ) 2 k''(x) = \frac{1}{1+x^2} + \frac{1 - x^2}{(1+x^2)^2} k ′′ ( x ) = 1 + x 2 1 + ( 1 + x 2 ) 2 1 − x 2 当
x → 0 + x \to 0^+ x → 0 +
,
h ′ ′ ( 0 ) = 2 π h''(0) = 2\pi h ′′ ( 0 ) = 2 π
,
k ′ ′ ( 0 ) = 2 k''(0) = 2 k ′′ ( 0 ) = 2
。 因此,
lim x → 0 + g ( x ) = lim x → 0 + h ( x ) k ( x ) = h ′ ′ ( 0 ) k ′ ′ ( 0 ) = 2 π 2 = π \lim_{x \to 0^+} g(x) = \lim_{x \to 0^+} \frac{h(x)}{k(x)} = \frac{h''(0)}{k''(0)} = \frac{2\pi}{2} = \pi x → 0 + lim g ( x ) = x → 0 + lim k ( x ) h ( x ) = k ′′ ( 0 ) h ′′ ( 0 ) = 2 2 π = π 故极限为
π \pi π
。
16 (本题满分 7 分)
计算二重积分
∬ D y 2 − x y d x d y \iint_D \sqrt{y^2 - xy} \dx\dy ∬ D y 2 − x y d x d y
,其中
D D D
是由直线
y = x , y = 1 , x = 0 y = x,y = 1,x = 0 y = x , y = 1 , x = 0
所围成的平面区域.
【答案】
2 9 \dfrac{2}{9} 9 2
【解析】
计算二重积分
∬ D y 2 − x y d x d y \iint_D \sqrt{y^2 - xy} dx dy ∬ D y 2 − x y d x d y
,其中
D D D
是由直线
y = x y = x y = x
、
y = 1 y = 1 y = 1
、
x = 0 x = 0 x = 0
所围成的区域。 区域
D D D
可以表示为:
x x x
从
0 0 0
到
1 1 1
,
y y y
从
x x x
到
1 1 1
。 考虑先对
x x x
积分,则积分顺序可交换为:
y y y
从
0 0 0
到
1 1 1
,对于每个
y y y
,
x x x
从
0 0 0
到
y y y
。 于是,积分化为:
∬ D y 2 − x y d x d y = ∫ 0 1 ∫ 0 y y 2 − x y d x d y \iint_D \sqrt{y^2 - xy} dx dy = \int_{0}^{1} \int_{0}^{y} \sqrt{y^2 - xy} dx dy ∬ D y 2 − x y d x d y = ∫ 0 1 ∫ 0 y y 2 − x y d x d y 计算内层积分:
∫ 0 y y 2 − x y d x = ∫ 0 y y ( y − x ) d x = y ∫ 0 y y − x d x \int_{0}^{y} \sqrt{y^2 - xy} dx = \int_{0}^{y} \sqrt{y(y - x)} dx = \sqrt{y} \int_{0}^{y} \sqrt{y - x} dx ∫ 0 y y 2 − x y d x = ∫ 0 y y ( y − x ) d x = y ∫ 0 y y − x d x 令
u = y − x u = y - x u = y − x
,则
d u = − d x du = -dx d u = − d x
,积分限变为:当
x = 0 x = 0 x = 0
时,
u = y u = y u = y
;当
x = y x = y x = y
时,
u = 0 u = 0 u = 0
。 于是,
∫ 0 y y − x d x = ∫ y 0 u ( − d u ) = ∫ 0 y u 1 / 2 d u = [ 2 3 u 3 / 2 ] 0 y = 2 3 y 3 / 2 \int_{0}^{y} \sqrt{y - x} dx = \int_{y}^{0} \sqrt{u} (-du) = \int_{0}^{y} u^{1/2} du = \left[ \frac{2}{3} u^{3/2} \right]_{0}^{y} = \frac{2}{3} y^{3/2} ∫ 0 y y − x d x = ∫ y 0 u ( − d u ) = ∫ 0 y u 1/2 d u = [ 3 2 u 3/2 ] 0 y = 3 2 y 3/2 因此,
∫ 0 y y 2 − x y d x = y ⋅ 2 3 y 3 / 2 = 2 3 y 2 \int_{0}^{y} \sqrt{y^2 - xy} dx = \sqrt{y} \cdot \frac{2}{3} y^{3/2} = \frac{2}{3} y^2 ∫ 0 y y 2 − x y d x = y ⋅ 3 2 y 3/2 = 3 2 y 2 代入二重积分:
∫ 0 1 2 3 y 2 d y = 2 3 ∫ 0 1 y 2 d y = 2 3 ⋅ [ 1 3 y 3 ] 0 1 = 2 3 ⋅ 1 3 = 2 9 \int_{0}^{1} \frac{2}{3} y^2 dy = \frac{2}{3} \int_{0}^{1} y^2 dy = \frac{2}{3} \cdot \left[ \frac{1}{3} y^3 \right]_{0}^{1} = \frac{2}{3} \cdot \frac{1}{3} = \frac{2}{9} ∫ 0 1 3 2 y 2 d y = 3 2 ∫ 0 1 y 2 d y = 3 2 ⋅ [ 3 1 y 3 ] 0 1 = 3 2 ⋅ 3 1 = 9 2 故二重积分的值为
2 9 \dfrac{2}{9} 9 2
。
17 (本题满分 10 分)
同试卷 2 第 19 题
18 (本题满分 8 分)
在
x O y xOy x O y
坐标平面上,连续曲线
L L L
过点
M ( 1 , 0 ) M\left(1,0 \right) M ( 1 , 0 )
,
其上任意点
P ( x , y ) P\left(x,y \right) P ( x , y )
(
x ≠ 0 x \ne 0 x = 0
)处的切线斜率与直线
O P OP OP
的斜率之差等于
a x ax a x
(常数
a > 0 a > 0 a > 0
).
(1) 求
L L L
的方程;
(2) 当
L L L
与直线
y = a x y = ax y = a x
所围成平面图形的面积为
8 3 \frac{8}{3} 3 8
时,确定
a a a
的值.
【答案】 (1)
L L L
的方程为
y = a x ( x − 1 ) y = a x (x - 1) y = a x ( x − 1 ) (2)
a = 2 a = 2 a = 2
【解析】 (I) 设所求的曲线方程为
y = y ( x ) y = y(x) y = y ( x )
,按题意有
y ′ − y x = a x y' - \frac{y}{x} = ax y ′ − x y = a x
,而且有初始条件
y ( 1 ) = 0 y(1) = 0 y ( 1 ) = 0
。解一阶线性微分方程,得到
y = e ∫ 1 x d x [ ∫ a x e − ∫ 1 x d x d x + C ] = x [ ∫ a d x + C ] = x ( a x + C ) .
y = e^{\int \frac{1}{x} \, dx} \left[ \int a x e^{-\int \frac{1}{x} \, dx} \, dx + C \right] = x \left[ \int a \, dx + C \right] = x(ax + C).
y = e ∫ x 1 d x [ ∫ a x e − ∫ x 1 d x d x + C ] = x [ ∫ a d x + C ] = x ( a x + C ) . 再由
y ( 1 ) = 0 y(1) = 0 y ( 1 ) = 0
得
C = − a C = -a C = − a
,于是所求的曲线方程为
y = a x ( x − 1 ) y = ax(x - 1) y = a x ( x − 1 )
。
(II) 直线
y = a x y = ax y = a x
与曲线
y = a x ( x − 1 ) y = ax(x - 1) y = a x ( x − 1 )
的交点为
( 0 , 0 ) (0, 0) ( 0 , 0 )
与
( 2 , 2 a ) (2, 2a) ( 2 , 2 a )
。所以直线
y = a x y = ax y = a x
与曲线
y = a x ( x − 1 ) y = ax(x - 1) y = a x ( x − 1 )
所围平面图形的面积为
S ( a ) = ∫ 0 2 [ a x − a x ( x − 1 ) ] d x = ∫ 0 2 [ 2 a x − a x 2 ] d x = 4 3 a .
S(a) = \int_0^2 [ax - ax(x - 1)] \, dx = \int_0^2 [2ax - ax^2] \, dx = \frac{4}{3}a.
S ( a ) = ∫ 0 2 [ a x − a x ( x − 1 )] d x = ∫ 0 2 [ 2 a x − a x 2 ] d x = 3 4 a . 于是按题意得
4 3 a = 8 3 \frac{4}{3}a = \frac{8}{3} 3 4 a = 3 8
,故
a = 2 a = 2 a = 2
。
19 (本题满分 10 分)
求幂级数
∑ n = 1 ∞ ( − 1 ) n − 1 x 2 n + 1 n ( 2 n − 1 ) \sum_{n = 1}^{\infty}\frac{(- 1)^{n - 1}x^{2n + 1}}{n(2n - 1)} ∑ n = 1 ∞ n ( 2 n − 1 ) ( − 1 ) n − 1 x 2 n + 1
的收敛域及和函数
S ( x ) S(x) S ( x )
.
【答案】 收敛域为
[ − 1 , 1 ] [-1, 1] [ − 1 , 1 ]
,和函数为
S ( x ) = 2 x 2 arctan x − x ln ( 1 + x 2 ) S(x) = 2x^2 \arctan x - x \ln(1 + x^2) S ( x ) = 2 x 2 arctan x − x ln ( 1 + x 2 )
。
【解析】 记
u n = ( − 1 ) n − 1 x 2 n + 1 n ( 2 n − 1 ) u_n = \frac{(-1)^{n-1} x^{2n+1}}{n(2n-1)} u n = n ( 2 n − 1 ) ( − 1 ) n − 1 x 2 n + 1
,则有
lim n → ∞ ∣ u n + 1 u n ∣ = x 2 \lim_{n \to \infty} \left| \frac{u_{n+1}}{u_n} \right| = x^2 lim n → ∞ u n u n + 1 = x 2
。所以当
x 2 < 1 x^2 < 1 x 2 < 1
即
∣ x ∣ < 1 |x| < 1 ∣ x ∣ < 1
时,级数绝对收敛;当
x 2 > 1 x^2 > 1 x 2 > 1
,即
∣ x ∣ > 1 |x| > 1 ∣ x ∣ > 1
时,级数发散;在
x = ± 1 x = \pm 1 x = ± 1
处
u n = ± ( − 1 ) n − 1 n ( 2 n − 1 ) u_n = \frac{\pm (-1)^{n-1}}{n(2n-1)} u n = n ( 2 n − 1 ) ± ( − 1 ) n − 1
,级数
∑ n = 1 ∞ u n \sum_{n=1}^\infty u_n ∑ n = 1 ∞ u n
绝对收敛;从而级数的收敛域为
[ − 1 , 1 ] [-1,1] [ − 1 , 1 ]
。由于
∑ n = 1 ∞ ( − 1 ) n − 1 x 2 n + 1 n ( 2 n − 1 ) = x ∑ n = 1 ∞ ( − 1 ) n − 1 x 2 n n ( 2 n − 1 ) ,
\sum_{n=1}^\infty \frac{(-1)^{n-1} x^{2n+1}}{n(2n-1)} = x \sum_{n=1}^\infty \frac{(-1)^{n-1} x^{2n}}{n(2n-1)},
n = 1 ∑ ∞ n ( 2 n − 1 ) ( − 1 ) n − 1 x 2 n + 1 = x n = 1 ∑ ∞ n ( 2 n − 1 ) ( − 1 ) n − 1 x 2 n , 令
f ( x ) = ∑ n = 1 ∞ ( − 1 ) n − 1 x 2 n n ( 2 n − 1 ) ( − 1 < x < 1 ) f(x) = \sum_{n=1}^\infty \frac{(-1)^{n-1} x^{2n}}{n(2n-1)} \quad (-1 < x < 1) f ( x ) = ∑ n = 1 ∞ n ( 2 n − 1 ) ( − 1 ) n − 1 x 2 n ( − 1 < x < 1 )
,则有
f ′ ( x ) = ∑ n = 1 ∞ 2 ( − 1 ) n − 1 x 2 n − 1 2 n − 1 , f ′ ′ ( x ) = 2 ∑ n = 1 ∞ ( − 1 ) n − 1 x 2 n − 2 = 2 1 + x 2 .
f'(x) = \sum_{n=1}^\infty \frac{2(-1)^{n-1} x^{2n-1}}{2n-1}, \quad f''(x) = 2 \sum_{n=1}^\infty (-1)^{n-1} x^{2n-2} = \frac{2}{1+x^2}.
f ′ ( x ) = n = 1 ∑ ∞ 2 n − 1 2 ( − 1 ) n − 1 x 2 n − 1 , f ′′ ( x ) = 2 n = 1 ∑ ∞ ( − 1 ) n − 1 x 2 n − 2 = 1 + x 2 2 . 从而有
f ′ ( x ) = f ′ ( 0 ) + ∫ 0 x f ′ ′ ( t ) d t = 0 + ∫ 0 x 2 1 + t 2 d t = 2 arctan x ,
f'(x) = f'(0) + \int_0^x f''(t)\,dt = 0 + \int_0^x \frac{2}{1+t^2}\,dt = 2 \arctan x,
f ′ ( x ) = f ′ ( 0 ) + ∫ 0 x f ′′ ( t ) d t = 0 + ∫ 0 x 1 + t 2 2 d t = 2 arctan x , f ( x ) = f ( 0 ) + ∫ 0 x f ′ ( t ) d t = 0 + 2 ∫ 0 x arctan t d t = 2 [ t arctan t ] 0 x − 2 ∫ 0 x d t 1 + t 2 = 2 x arctan x − ln ( 1 + x 2 ) .
\begin{align*}
f(x) &= f(0) + \int_0^x f'(t)\,dt = 0 + 2 \int_0^x \arctan t\,dt \\
&= 2 \bigl[ t \arctan t \bigr]_0^x - 2 \int_0^x \frac{dt}{1+t^2} \\
&= 2x \arctan x - \ln(1+x^2).
\end{align*}
f ( x ) = f ( 0 ) + ∫ 0 x f ′ ( t ) d t = 0 + 2 ∫ 0 x arctan t d t = 2 [ t arctan t ] 0 x − 2 ∫ 0 x 1 + t 2 d t = 2 x arctan x − ln ( 1 + x 2 ) . 于是
∑ n = 1 ∞ ( − 1 ) n − 1 x 2 n + 1 n ( 2 n − 1 ) = 2 x 2 arctan x − x ln ( 1 + x 2 ) , − 1 < x < 1.
\sum_{n=1}^\infty \frac{(-1)^{n-1} x^{2n+1}}{n(2n-1)} = 2x^2 \arctan x - x \ln(1+x^2), \quad -1 < x < 1.
n = 1 ∑ ∞ n ( 2 n − 1 ) ( − 1 ) n − 1 x 2 n + 1 = 2 x 2 arctan x − x ln ( 1 + x 2 ) , − 1 < x < 1. 又因为在
x = ± 1 x = \pm 1 x = ± 1
处级数收敛,右边和函数的表达式在
x = ± 1 x = \pm 1 x = ± 1
处连续,因此在
x = ± 1 x = \pm 1 x = ± 1
处上式仍成立,从而有
S ( x ) = ∑ n = 1 ∞ ( − 1 ) n − 1 x 2 n + 1 n ( 2 n − 1 ) = 2 x 2 arctan x − x ln ( 1 + x 2 ) , − 1 ≤ x ≤ 1.
S(x) = \sum_{n=1}^\infty \frac{(-1)^{n-1} x^{2n+1}}{n(2n-1)} = 2x^2 \arctan x - x \ln(1+x^2), \quad -1 \leq x \leq 1.
S ( x ) = n = 1 ∑ ∞ n ( 2 n − 1 ) ( − 1 ) n − 1 x 2 n + 1 = 2 x 2 arctan x − x ln ( 1 + x 2 ) , − 1 ≤ x ≤ 1. 20 (本题满分 13 分)
设
4 4 4
维向量组
α 1 = ( 1 + a , 1 , 1 , 1 ) T \alpha_1 = (1 + a,1,1,1)^T α 1 = ( 1 + a , 1 , 1 , 1 ) T
,
α 2 = ( 2 , 2 + a , 2 , 2 ) T \alpha_2 = (2,2 + a,2,2)^T α 2 = ( 2 , 2 + a , 2 , 2 ) T
,
α 3 = ( 3 , 3 , 3 + a , 3 ) T \alpha_3 = (3,3,3 + a,3)^T α 3 = ( 3 , 3 , 3 + a , 3 ) T
,
α 4 = ( 4 , 4 , 4 , 4 + a ) T \alpha_4 = (4,4,4,4 + a)^T α 4 = ( 4 , 4 , 4 , 4 + a ) T
.
问
a a a
为何值时
α 1 , α 2 , α 3 , α 4 \alpha_1,\alpha_2,\alpha_3,\alpha_4 α 1 , α 2 , α 3 , α 4
线性相关?
当
α 1 , α 2 , α 3 , α 4 \alpha_1,\alpha_2,\alpha_3,\alpha_4 α 1 , α 2 , α 3 , α 4
线性相关时,
求其一个极大线性无关组,并将其余向量用该极大线性无关组线性表示.
【答案】 当
a = 0 a = 0 a = 0
或
a = − 10 a = -10 a = − 10
时,向量组
α 1 , α 2 , α 3 , α 4 \alpha_1, \alpha_2, \alpha_3, \alpha_4 α 1 , α 2 , α 3 , α 4
线性相关。
当
a = 0 a = 0 a = 0
时,一个极大线性无关组为
α 1 \alpha_1 α 1
,且
α 2 = 2 α 1 \alpha_2 = 2\alpha_1 α 2 = 2 α 1
,
α 3 = 3 α 1 \alpha_3 = 3\alpha_1 α 3 = 3 α 1
,
α 4 = 4 α 1 \alpha_4 = 4\alpha_1 α 4 = 4 α 1
。 当
a = − 10 a = -10 a = − 10
时,一个极大线性无关组为
α 1 , α 2 , α 3 \alpha_1, \alpha_2, \alpha_3 α 1 , α 2 , α 3
,且
α 4 = − α 1 − α 2 − α 3 \alpha_4 = -\alpha_1 - \alpha_2 - \alpha_3 α 4 = − α 1 − α 2 − α 3
。 【解析】 记
A = ( a 1 , a 2 , a 3 , a 4 ) A = (a_1, a_2, a_3, a_4) A = ( a 1 , a 2 , a 3 , a 4 )
,对
A A A
作初等行变换,得到
A = ( 1 + a 2 3 4 1 2 + a 3 4 1 2 3 + a 4 1 2 3 4 + a ) → ( 1 + a 2 3 4 − a a 0 0 − a 0 a 0 − a 0 0 a ) = B .
A = \begin{pmatrix}
1+a & 2 & 3 & 4 \\
1 & 2+a & 3 & 4 \\
1 & 2 & 3+a & 4 \\
1 & 2 & 3 & 4+a
\end{pmatrix}
\rightarrow
\begin{pmatrix}
1+a & 2 & 3 & 4 \\
-a & a & 0 & 0 \\
-a & 0 & a & 0 \\
-a & 0 & 0 & a
\end{pmatrix} = B.
A = 1 + a 1 1 1 2 2 + a 2 2 3 3 3 + a 3 4 4 4 4 + a → 1 + a − a − a − a 2 a 0 0 3 0 a 0 4 0 0 a = B . 当
a = 0 a = 0 a = 0
时 ,
r ( A ) = r ( B ) = 1 r(A) = r(B) = 1 r ( A ) = r ( B ) = 1
,因而
a 1 , a 2 , a 3 , a 4 a_1, a_2, a_3, a_4 a 1 , a 2 , a 3 , a 4
线性相关。此时
a 1 a_1 a 1
为
a 1 , a 2 , a 3 , a 4 a_1, a_2, a_3, a_4 a 1 , a 2 , a 3 , a 4
的一个极大线性无关组,且
a 2 = 2 a 1 , a 3 = 3 a 1 , a 4 = 4 a 1 a_2 = 2a_1, a_3 = 3a_1, a_4 = 4a_1 a 2 = 2 a 1 , a 3 = 3 a 1 , a 4 = 4 a 1
。
当
a ≠ 0 a \ne 0 a = 0
时 ,再对
B B B
作初等行变换,得到
B → ( 1 + a 2 3 4 − 1 1 0 0 − 1 0 1 0 − 1 0 0 1 ) → ( a + 10 0 0 0 1 − 1 0 0 1 0 − 1 0 1 0 0 − 1 ) = C = ( γ 1 , γ 2 , γ 3 , γ 4 ) .
B \rightarrow
\begin{pmatrix}
1+a & 2 & 3 & 4 \\
-1 & 1 & 0 & 0 \\
-1 & 0 & 1 & 0 \\
-1 & 0 & 0 & 1
\end{pmatrix}
\rightarrow
\begin{pmatrix}
a+10 & 0 & 0 & 0 \\
1 & -1 & 0 & 0 \\
1 & 0 & -1 & 0 \\
1 & 0 & 0 & -1
\end{pmatrix} = C = (\gamma_1, \gamma_2, \gamma_3, \gamma_4).
B → 1 + a − 1 − 1 − 1 2 1 0 0 3 0 1 0 4 0 0 1 → a + 10 1 1 1 0 − 1 0 0 0 0 − 1 0 0 0 0 − 1 = C = ( γ 1 , γ 2 , γ 3 , γ 4 ) . 若
a ≠ − 10 a \ne -10 a = − 10
,则
C C C
的秩为 4,故
a 1 , a 2 , a 3 , a 4 a_1, a_2, a_3, a_4 a 1 , a 2 , a 3 , a 4
线性无关。
若
a = − 10 a = -10 a = − 10
,则
C C C
的秩为 3,故
a 1 , a 2 , a 3 , a 4 a_1, a_2, a_3, a_4 a 1 , a 2 , a 3 , a 4
线性相关。由于
γ 2 , γ 3 , γ 4 \gamma_2, \gamma_3, \gamma_4 γ 2 , γ 3 , γ 4
是
γ 1 , γ 2 , γ 3 , γ 4 \gamma_1, \gamma_2, \gamma_3, \gamma_4 γ 1 , γ 2 , γ 3 , γ 4
的一个极大线性无关组,且
γ 1 = − γ 2 − γ 3 − γ 4 \gamma_1 = -\gamma_2 - \gamma_3 - \gamma_4 γ 1 = − γ 2 − γ 3 − γ 4
,于是
a 2 , a 3 , a 4 a_2, a_3, a_4 a 2 , a 3 , a 4
是
a 1 , a 2 , a 3 , a 4 a_1, a_2, a_3, a_4 a 1 , a 2 , a 3 , a 4
的一个极大线性无关组,且
a 1 = − a 2 − a 3 − a 4 a_1 = -a_2 - a_3 - a_4 a 1 = − a 2 − a 3 − a 4
。
21 (本题满分 13 分)
设
3 3 3
阶实对称矩阵
A A A
的各行元素之和均为
3 3 3
,
向量
α 1 = ( − 1 , 2 , − 1 ) T \alpha_1 = \left(- 1,2, - 1 \right)^T α 1 = ( − 1 , 2 , − 1 ) T
,
α 2 = ( 0 , − 1 , 1 ) T \alpha_2 = \left(0, - 1,1 \right)^T α 2 = ( 0 , − 1 , 1 ) T
是线性方程组
A x = 0 Ax = 0 A x = 0
的两个解.
(1) 求
A A A
的特征值与特征向量;
(2) 求正交矩阵
Q Q Q
和对角矩阵
Λ \Lambda Λ
,使得
Q T A Q = Λ Q^T AQ = \Lambda Q T A Q = Λ
;
(3) 求
A A A
及
( A − 3 2 E ) 6 \left(A - \frac{3}{2}E \right)^6 ( A − 2 3 E ) 6
,其中
E E E
为
3 3 3
阶单位矩阵.
【答案】 (1) 特征值与特征向量 矩阵
A A A
的特征值为
λ 1 = λ 2 = 0 \lambda_1 = \lambda_2 = 0 λ 1 = λ 2 = 0
(二重),
λ 3 = 3 \lambda_3 = 3 λ 3 = 3
(一重)。 属于特征值
0 0 0
的特征向量为
k 1 α 1 + k 2 α 2 k_1 \alpha_1 + k_2 \alpha_2 k 1 α 1 + k 2 α 2
,其中
k 1 , k 2 k_1, k_2 k 1 , k 2
不全为零;属于特征值
3 3 3
的特征向量为
k 3 ( 1 , 1 , 1 ) T k_3 (1,1,1)^\text{T} k 3 ( 1 , 1 , 1 ) T
,其中
k 3 ≠ 0 k_3 \ne 0 k 3 = 0
。
(2) 正交矩阵
Q Q Q
与对角矩阵
Λ \Lambda Λ
Q = ( − 6 6 − 2 2 3 3 6 3 0 3 3 − 6 6 2 2 3 3 ) , Λ = ( 0 0 0 0 0 0 0 0 3 ) .
Q = \begin{pmatrix}
-\dfrac{\sqrt{6}}{6} & -\dfrac{\sqrt{2}}{2} & \dfrac{\sqrt{3}}{3} \\[6pt]
\dfrac{\sqrt{6}}{3} & 0 & \dfrac{\sqrt{3}}{3} \\[6pt]
-\dfrac{\sqrt{6}}{6} & \dfrac{\sqrt{2}}{2} & \dfrac{\sqrt{3}}{3}
\end{pmatrix}, \quad \Lambda = \begin{pmatrix}
0 & 0 & 0 \\
0 & 0 & 0 \\
0 & 0 & 3
\end{pmatrix}.
Q = − 6 6 3 6 − 6 6 − 2 2 0 2 2 3 3 3 3 3 3 , Λ = 0 0 0 0 0 0 0 0 3 . 满足
Q T A Q = Λ Q^\text{T} A Q = \Lambda Q T A Q = Λ
。
(3) 矩阵
A A A
与
( A − 3 2 E ) 6 \left(A - \dfrac{3}{2}E\right)^6 ( A − 2 3 E ) 6
A = ( 1 1 1 1 1 1 1 1 1 ) , ( A − 3 2 E ) 6 = ( 3 2 ) 6 E = 729 64 E .
A = \begin{pmatrix}
1 & 1 & 1 \\
1 & 1 & 1 \\
1 & 1 & 1
\end{pmatrix}, \quad \left(A - \frac{3}{2}E\right)^6 = \left(\frac{3}{2}\right)^6 E = \frac{729}{64} E.
A = 1 1 1 1 1 1 1 1 1 , ( A − 2 3 E ) 6 = ( 2 3 ) 6 E = 64 729 E . 【解析】
(I) 由题设条件
A α 1 = 0 = 0 α 1 A\alpha_1 = 0 = 0\alpha_1 A α 1 = 0 = 0 α 1
,
A α 2 = 0 = 0 α 2 A\alpha_2 = 0 = 0\alpha_2 A α 2 = 0 = 0 α 2
, 故
α 1 , α 2 \alpha_1, \alpha_2 α 1 , α 2
是
A A A
的对应于
λ = 0 \lambda = 0 λ = 0
的特征向量,又因为
α 1 , α 2 \alpha_1, \alpha_2 α 1 , α 2
线性无关,故
λ = 0 \lambda = 0 λ = 0
至少是
A A A
的二重特征值。又因为
A A A
的每行元素之和为 3,所以有
A ( 1 , 1 , 1 ) T = ( 3 , 3 , 3 ) T = 3 ( 1 , 1 , 1 ) T ,
A(1,1,1)^T = (3,3,3)^T = 3(1,1,1)^T,
A ( 1 , 1 , 1 ) T = ( 3 , 3 , 3 ) T = 3 ( 1 , 1 , 1 ) T , 所以
α 3 = ( 1 , 1 , 1 ) T \alpha_3 = (1,1,1)^T α 3 = ( 1 , 1 , 1 ) T
是
A A A
的对应于特征值
λ 3 = 3 \lambda_3 = 3 λ 3 = 3
的特征向量,从而知
λ = 0 \lambda = 0 λ = 0
是二重特征值。于是
A A A
的特征值为
0 , 0 , 3 0, 0, 3 0 , 0 , 3
;属于 0 的特征向量是
k 1 α 1 + k 2 α 2 k_1\alpha_1 + k_2\alpha_2 k 1 α 1 + k 2 α 2
,
k 1 , k 2 k_1, k_2 k 1 , k 2
不都为 0;属于 3 的特征向量是
k 3 α 3 k_3\alpha_3 k 3 α 3
,
k 3 ≠ 0 k_3 \ne 0 k 3 = 0
。
(II) 将特征向量
α 1 , α 2 \alpha_1, \alpha_2 α 1 , α 2
正交化得
β 1 = α 1 = ( − 1 , 2 , − 1 ) T , β 2 = ( − 1 2 , 0 , 1 2 ) .
\beta_1 = \alpha_1 = (-1, 2, -1)^T, \quad \beta_2 = \left(-\frac{1}{2}, 0, \frac{1}{2}\right).
β 1 = α 1 = ( − 1 , 2 , − 1 ) T , β 2 = ( − 2 1 , 0 , 2 1 ) . 再将
β 1 , β 2 , α 3 \beta_1, \beta_2, \alpha_3 β 1 , β 2 , α 3
单位化,得
η 1 = ( − 6 6 , 6 3 , − 6 6 ) T , η 2 = ( − 2 2 , 0 , 2 2 ) T , η 3 = ( 3 3 , 3 3 , 3 3 ) T .
\eta_1 = \left(-\frac{\sqrt{6}}{6}, \frac{\sqrt{6}}{3}, -\frac{\sqrt{6}}{6}\right)^T, \quad
\eta_2 = \left(-\frac{\sqrt{2}}{2}, 0, \frac{\sqrt{2}}{2}\right)^T, \quad
\eta_3 = \left(\frac{\sqrt{3}}{3}, \frac{\sqrt{3}}{3}, \frac{\sqrt{3}}{3}\right)^T.
η 1 = ( − 6 6 , 3 6 , − 6 6 ) T , η 2 = ( − 2 2 , 0 , 2 2 ) T , η 3 = ( 3 3 , 3 3 , 3 3 ) T . 令
Q = ( η 1 , η 2 , η 3 ) Q = (\eta_1, \eta_2, \eta_3) Q = ( η 1 , η 2 , η 3 )
,则
Q Q Q
是正交矩阵,并且
Q T A Q = Q − 1 A Q = ( 0 0 0 0 0 0 0 0 3 ) .
Q^T A Q = Q^{-1} A Q =
\begin{pmatrix}
0 & 0 & 0 \\
0 & 0 & 0 \\
0 & 0 & 3
\end{pmatrix}.
Q T A Q = Q − 1 A Q = 0 0 0 0 0 0 0 0 3 . (Ⅲ) 由
Q T A Q = Λ Q^T A Q = \Lambda Q T A Q = Λ
,其中
Q T = Q − 1 Q^T = Q^{-1} Q T = Q − 1
,得到
A = Q Λ Q T = ( − 6 6 − 2 2 3 3 6 3 0 3 3 − 6 6 2 2 3 3 ) ( 0 0 3 ) ( − 6 6 6 3 − 6 6 − 2 2 0 2 2 3 3 3 3 3 3 ) = ( 1 1 1 1 1 1 1 1 1 ) ,
\begin{align*}
A = Q \Lambda Q^T
&= \begin{pmatrix}
\dfrac{-\sqrt{6}}{6} & \dfrac{-\sqrt{2}}{2} & \dfrac{\sqrt{3}}{3} \\[8pt]
\dfrac{\sqrt{6}}{3} & 0 & \dfrac{\sqrt{3}}{3} \\[8pt]
\dfrac{-\sqrt{6}}{6} & \dfrac{\sqrt{2}}{2} & \dfrac{\sqrt{3}}{3}
\end{pmatrix}
\begin{pmatrix}
0 & & \\
& 0 & \\
& & 3
\end{pmatrix}
\begin{pmatrix}
\dfrac{-\sqrt{6}}{6} & \dfrac{\sqrt{6}}{3} & \dfrac{-\sqrt{6}}{6} \\[8pt]
\dfrac{-\sqrt{2}}{2} & 0 & \dfrac{\sqrt{2}}{2} \\[8pt]
\dfrac{\sqrt{3}}{3} & \dfrac{\sqrt{3}}{3} & \dfrac{\sqrt{3}}{3}
\end{pmatrix} \\
&= \begin{pmatrix}
1 & 1 & 1 \\
1 & 1 & 1 \\
1 & 1 & 1
\end{pmatrix},
\end{align*}
A = Q Λ Q T = 6 − 6 3 6 6 − 6 2 − 2 0 2 2 3 3 3 3 3 3 0 0 3 6 − 6 2 − 2 3 3 3 6 0 3 3 6 − 6 2 2 3 3 = 1 1 1 1 1 1 1 1 1 , ( A − 3 2 E ) 6 = ( Q Λ Q T − 3 2 E ) 6 = ( Q ( Λ − 3 2 E ) Q T ) 6 = Q ( Λ − 3 2 E ) 6 Q T
\left(A - \frac{3}{2}E\right)^6 = \left(Q \Lambda Q^T - \frac{3}{2}E\right)^6 = \left(Q \left(\Lambda - \frac{3}{2}E\right) Q^T\right)^6 = Q \left(\Lambda - \frac{3}{2}E\right)^6 Q^T
( A − 2 3 E ) 6 = ( Q Λ Q T − 2 3 E ) 6 = ( Q ( Λ − 2 3 E ) Q T ) 6 = Q ( Λ − 2 3 E ) 6 Q T = Q ( − 3 2 − 3 2 3 2 ) 6 Q T = ( 3 2 ) 6 Q E Q T = ( 3 2 ) 6 E .
= Q
\begin{pmatrix}
-\dfrac{3}{2} & & \\
& -\dfrac{3}{2} & \\
& & \dfrac{3}{2}
\end{pmatrix}^6
Q^T = \left(\frac{3}{2}\right)^6 Q E Q^T = \left(\frac{3}{2}\right)^6 E.
= Q − 2 3 − 2 3 2 3 6 Q T = ( 2 3 ) 6 QE Q T = ( 2 3 ) 6 E . 22 (本题满分 13 分)
随机变量
x x x
的概率密度为
f X ( x ) = { 1 2 , − 1 < x < 0 ; 1 4 , 0 ≤ x < 2 ; 0 , 其他 . f_X(x) = \begin{cases}
\frac{1}{2}, & -1 < x < 0; \\
\frac{1}{4}, & 0 \le x < 2; \\
0, & \text{其他}.
\end{cases} f X ( x ) = ⎩ ⎨ ⎧ 2 1 , 4 1 , 0 , − 1 < x < 0 ; 0 ≤ x < 2 ; 其他 . 令
Y = X 2 Y = X^2 Y = X 2
,
F ( x , y ) F(x,y) F ( x , y )
为二维随机变量
( X , Y ) (X,Y) ( X , Y )
的分布函数.求
(1)
Y Y Y
的概率密度
f Y ( y ) f_Y(y) f Y ( y )
;
(2)
Cov ( X , Y ) \Cov(X,Y) Cov ( X , Y )
;
(3)
F ( − 1 2 , 4 ) F\left(-\frac{1}{2},4\right) F ( − 2 1 , 4 )
.
【答案】 (1)
Y Y Y
的概率密度为
f Y ( y ) = { 3 8 y − 1 / 2 , 0 ≤ y < 1 1 8 y − 1 / 2 , 1 ≤ y < 4 0 , f_Y(y) =
\begin{cases}
\frac{3}{8} y^{-1/2}, & 0 \le y < 1 \\
\frac{1}{8} y^{-1/2}, & 1 \le y < 4 \\
0, & \text{}
\end{cases} f Y ( y ) = ⎩ ⎨ ⎧ 8 3 y − 1/2 , 8 1 y − 1/2 , 0 , 0 ≤ y < 1 1 ≤ y < 4 (2)
Cov ( X , Y ) = 2 3 \Cov(X,Y) = \frac{2}{3} Cov ( X , Y ) = 3 2 (3)
F ( − 1 2 , 4 ) = 1 4 F\left(-\frac{1}{2},4\right) = \frac{1}{4} F ( − 2 1 , 4 ) = 4 1
【解析】 (Ⅰ) 因为
F Y ( y ) = P { Y ≤ y } = P { X 2 ≤ y } F_Y(y) = P\{Y \leq y\} = P\{X^2 \leq y\} F Y ( y ) = P { Y ≤ y } = P { X 2 ≤ y }
,分情况讨论:
当
y < 0 y < 0 y < 0
时,
F Y ( y ) = 0 F_Y(y) = 0 F Y ( y ) = 0
;
当
0 ≤ y < 1 0 \leq y < 1 0 ≤ y < 1
时,
F Y ( y ) = P ( − y ≤ X ≤ y ) = ∫ − y 0 1 2 d x + ∫ 0 y 1 4 d x = 3 4 y ;
F_Y(y) = P(-\sqrt{y} \leq X \leq \sqrt{y}) = \int_{-\sqrt{y}}^{0} \frac{1}{2} \, dx + \int_{0}^{\sqrt{y}} \frac{1}{4} \, dx = \frac{3}{4} \sqrt{y};
F Y ( y ) = P ( − y ≤ X ≤ y ) = ∫ − y 0 2 1 d x + ∫ 0 y 4 1 d x = 4 3 y ; 当
1 ≤ y < 4 1 \leq y < 4 1 ≤ y < 4
时,
F Y ( y ) = P ( − y ≤ X ≤ y ) = ∫ − 1 0 1 2 d x + ∫ 0 y 1 4 d x = 1 2 + 1 4 y ;
F_Y(y) = P(-\sqrt{y} \leq X \leq \sqrt{y}) = \int_{-1}^{0} \frac{1}{2} \, dx + \int_{0}^{\sqrt{y}} \frac{1}{4} \, dx = \frac{1}{2} + \frac{1}{4} \sqrt{y};
F Y ( y ) = P ( − y ≤ X ≤ y ) = ∫ − 1 0 2 1 d x + ∫ 0 y 4 1 d x = 2 1 + 4 1 y ; 当
y ≥ 4 y \geq 4 y ≥ 4
时,
F Y ( y ) = 1 F_Y(y) = 1 F Y ( y ) = 1
。
综上所述,有
F Y ( y ) = { 0 , y < 0 ; 3 4 y , 0 ≤ y < 1 ; 1 2 + 1 4 y , 1 ≤ y < 4 ; 1 , y ≥ 4.
F_Y(y) =
\begin{cases}
0, & y < 0; \\
\frac{3}{4} \sqrt{y}, & 0 \leq y < 1; \\
\frac{1}{2} + \frac{1}{4} \sqrt{y}, & 1 \leq y < 4; \\
1, & y \geq 4.
\end{cases}
F Y ( y ) = ⎩ ⎨ ⎧ 0 , 4 3 y , 2 1 + 4 1 y , 1 , y < 0 ; 0 ≤ y < 1 ; 1 ≤ y < 4 ; y ≥ 4. 由概率密度是分布函数在对应区间上的微分,所以
f Y ( y ) = F Y ′ ( y ) = { 3 8 y , 0 < y < 1 ; 1 8 y , 1 ≤ y < 4 ; 0 , 其他 .
f_Y(y) = F_Y'(y) =
\begin{cases}
\frac{3}{8\sqrt{y}}, & 0 < y < 1; \\
\frac{1}{8\sqrt{y}}, & 1 \leq y < 4; \\
0, & \text{其他}.
\end{cases}
f Y ( y ) = F Y ′ ( y ) = ⎩ ⎨ ⎧ 8 y 3 , 8 y 1 , 0 , 0 < y < 1 ; 1 ≤ y < 4 ; 其他 . (II) 因为数学期望
E ( X ) = ∫ − ∞ + ∞ x f X ( x ) d x = ∫ − 1 0 x 2 d x + ∫ 0 2 x 4 d x = 1 4 ,
E(X) = \int_{-\infty}^{+\infty} x f_X(x) \, dx = \int_{-1}^{0} \frac{x}{2} \, dx + \int_{0}^{2} \frac{x}{4} \, dx = \frac{1}{4},
E ( X ) = ∫ − ∞ + ∞ x f X ( x ) d x = ∫ − 1 0 2 x d x + ∫ 0 2 4 x d x = 4 1 , E ( X 2 ) = ∫ − ∞ + ∞ x 2 f X ( x ) d x = ∫ − 1 0 x 2 2 d x + ∫ 0 2 x 2 4 d x = 5 6 ,
E(X^2) = \int_{-\infty}^{+\infty} x^2 f_X(x) \, dx = \int_{-1}^{0} \frac{x^2}{2} \, dx + \int_{0}^{2} \frac{x^2}{4} \, dx = \frac{5}{6},
E ( X 2 ) = ∫ − ∞ + ∞ x 2 f X ( x ) d x = ∫ − 1 0 2 x 2 d x + ∫ 0 2 4 x 2 d x = 6 5 , E ( X 3 ) = ∫ − ∞ + ∞ x 3 f X ( x ) d x = ∫ − 1 0 x 3 2 d x + ∫ 0 2 x 3 4 d x = 7 8 ,
E(X^3) = \int_{-\infty}^{+\infty} x^3 f_X(x) \, dx = \int_{-1}^{0} \frac{x^3}{2} \, dx + \int_{0}^{2} \frac{x^3}{4} \, dx = \frac{7}{8},
E ( X 3 ) = ∫ − ∞ + ∞ x 3 f X ( x ) d x = ∫ − 1 0 2 x 3 d x + ∫ 0 2 4 x 3 d x = 8 7 , 所以协方差
Cov ( X , Y ) = Cov ( X , X 2 ) = E ( X 3 ) − E ( X ) E ( X 2 ) = 7 8 − 1 4 × 5 6 = 2 3 .
\operatorname{Cov}(X, Y) = \operatorname{Cov}(X, X^2) = E(X^3) - E(X)E(X^2) = \frac{7}{8} - \frac{1}{4} \times \frac{5}{6} = \frac{2}{3}.
Cov ( X , Y ) = Cov ( X , X 2 ) = E ( X 3 ) − E ( X ) E ( X 2 ) = 8 7 − 4 1 × 6 5 = 3 2 . (III) 根据二维随机变量的定义有
F ( − 1 2 , 4 ) = P { X ⩽ − 1 2 , Y ⩽ 4 } = P { X ⩽ − 1 2 , X 2 ⩽ 4 }
F\left(-\frac{1}{2}, 4\right) = P\left\{ X \leqslant -\frac{1}{2}, Y \leqslant 4 \right\} = P\left\{ X \leqslant -\frac{1}{2}, X^2 \leqslant 4 \right\}
F ( − 2 1 , 4 ) = P { X ⩽ − 2 1 , Y ⩽ 4 } = P { X ⩽ − 2 1 , X 2 ⩽ 4 } = P { − 2 ⩽ X ⩽ − 1 2 } = ∫ − 1 − 1 2 1 2 d x = 1 4 .
= P\left\{ -2 \leqslant X \leqslant -\frac{1}{2} \right\} = \int_{-1}^{-\frac{1}{2}} \frac{1}{2} \, dx = \frac{1}{4}.
= P { − 2 ⩽ X ⩽ − 2 1 } = ∫ − 1 − 2 1 2 1 d x = 4 1 . 23 (本题满分 13 分)
设总体
X X X
的概率密度为
f ( x , θ ) = { θ , 0 < x < 1 , 1 − θ , 1 ≤ x < 2 , 0 , 其它 , f(x,\theta) = \begin{cases}
\theta , & 0 < x < 1, \\
1 - \theta , & 1 \le x < 2, \\
0, & \text{其它},
\end{cases} f ( x , θ ) = ⎩ ⎨ ⎧ θ , 1 − θ , 0 , 0 < x < 1 , 1 ≤ x < 2 , 其它 , 其中
θ \theta θ
是未知参数(
0 < θ < 1 0 < \theta < 1 0 < θ < 1
),
X 1 , X 2 ⋯ , X n X_1,X_2\cdots ,X_{n} X 1 , X 2 ⋯ , X n
为来自总体
X X X
的简单随机样本,
记
N N N
为样本值
x 1 , x 2 ⋯ , x n x_1,x_2\cdots ,x_n x 1 , x 2 ⋯ , x n
中小于
1 1 1
的个数,求:
(1)
θ \theta θ
的矩估计;
(2)
θ \theta θ
的最大似然估计.
【答案】 (1)
θ \theta θ
的矩估计为
θ ^ M = 3 2 − X ˉ \hat{\theta}_M = \frac{3}{2} - \bar{X} θ ^ M = 2 3 − X ˉ
,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
。 (2)
θ \theta θ
的最大似然估计为
θ ^ = N n \hat{\theta} = \frac{N}{n} θ ^ = n N
,其中
N N N
为样本中小于
1 1 1
的个数。
【解析】 (I) 由数学期望的定义有
E ( X ) = ∫ − ∞ + ∞ x f ( x ; θ ) d x = ∫ 0 1 θ x d x + ∫ 1 2 ( 1 − θ ) x d x
E(X) = \int_{-\infty}^{+\infty} x f(x; \theta)\,dx = \int_0^1 \theta x\,dx + \int_1^2 (1 - \theta)x\,dx
E ( X ) = ∫ − ∞ + ∞ x f ( x ; θ ) d x = ∫ 0 1 θ x d x + ∫ 1 2 ( 1 − θ ) x d x = 1 2 θ + 3 2 ( 1 − θ ) = 3 2 − θ .
= \frac{1}{2}\theta + \frac{3}{2}(1 - \theta) = \frac{3}{2} - \theta.
= 2 1 θ + 2 3 ( 1 − θ ) = 2 3 − θ . 用样本均值估计期望有
E X = X ‾ E X = \overline{X} EX = X
,即
3 2 − θ = X ‾ \frac{3}{2} - \theta = \overline{X} 2 3 − θ = X
,解得
θ = 3 2 − X ‾ \theta = \frac{3}{2} - \overline{X} θ = 2 3 − X
。所以参数
θ \theta θ
的矩估计为
θ ^ = 3 2 − X ‾ \hat{\theta} = \frac{3}{2} - \overline{X} θ ^ = 2 3 − X
,其中
X ‾ = 1 n ∑ i = 1 n X i \overline{X} = \frac{1}{n} \sum_{i=1}^n X_i X = n 1 ∑ i = 1 n X i
。
(II) 依题设,似然函数
L ( θ ) = { θ N ( 1 − θ ) n − N , 0 < x i 1 , x i 2 , … x i N < 1 , 1 ≤ x i N + 1 , x i N + 2 , … x i n < 2 ; 0 , 其他 .
L(\theta) =
\begin{cases}
\theta^N (1 - \theta)^{n - N}, & 0 < x_{i_1}, x_{i_2}, \ldots x_{i_N} < 1,\ 1 \le x_{i_{N+1}}, x_{i_{N+2}}, \ldots x_{i_n} < 2; \\
0, & \text{其他}.
\end{cases}
L ( θ ) = { θ N ( 1 − θ ) n − N , 0 , 0 < x i 1 , x i 2 , … x i N < 1 , 1 ≤ x i N + 1 , x i N + 2 , … x i n < 2 ; 其他 . 在
0 < x i 1 , x i 2 , … x i N < 1 0 < x_{i_1}, x_{i_2}, \ldots x_{i_N} < 1 0 < x i 1 , x i 2 , … x i N < 1
,
1 ≤ x i N + 1 , x i N + 2 , … x i n < 2 1 \le x_{i_{N+1}}, x_{i_{N+2}}, \ldots x_{i_n} < 2 1 ≤ x i N + 1 , x i N + 2 , … x i n < 2
时,等式两边同取对数得
ln L ( θ ) = N ln θ + ( n − N ) ln ( 1 − θ ) .
\ln L(\theta) = N \ln \theta + (n - N) \ln(1 - \theta).
ln L ( θ ) = N ln θ + ( n − N ) ln ( 1 − θ ) . 两边对
θ \theta θ
求导并令导数为零,得到
d ln L ( θ ) d θ = N θ − n − N 1 − θ = 0 ,
\frac{\mathrm{d} \ln L(\theta)}{\mathrm{d} \theta} = \frac{N}{\theta} - \frac{n - N}{1 - \theta} = 0,
d θ d ln L ( θ ) = θ N − 1 − θ n − N = 0 , 解得
θ = N n \theta = \frac{N}{n} θ = n N
,所以
θ \theta θ
的最大似然估计值为
θ ^ = N n \hat{\theta} = \frac{N}{n} θ ^ = n N
。