|
|
|
|
@ -159,6 +159,8 @@ $$A^n = 6^{n-1}\begin{bmatrix}3&-1\\-9&3\end{bmatrix} $$
|
|
|
|
|
a = \underline{\qquad\qquad}.
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
---
|
|
|
|
|
|
|
|
|
|
10. 设矩阵
|
|
|
|
|
$$
|
|
|
|
|
A = \begin{bmatrix}
|
|
|
|
|
@ -192,18 +194,16 @@ $$
|
|
|
|
|
$$
|
|
|
|
|
k= \underline{\qquad\qquad\qquad\qquad}.
|
|
|
|
|
$$
|
|
|
|
|
12.
|
|
|
|
|
$$
|
|
|
|
|
\underline{\qquad\qquad\qquad\qquad}.
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
12.
|
|
|
|
|
$$\underline{\qquad\qquad\qquad\qquad}$$
|
|
|
|
|
|
|
|
|
|
## 三、解答题,共五道,共64分
|
|
|
|
|
---
|
|
|
|
|
|
|
|
|
|
12. (10 分)计算 下面的$n$ 阶行列式
|
|
|
|
|
13. (20 分)计算 下面的两个$n$阶行列式
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
D_n = \begin{vmatrix}
|
|
|
|
|
K_n = \begin{vmatrix}
|
|
|
|
|
1 & 2 & 3 & \cdots & n-1 & n \\
|
|
|
|
|
2 & 1 & 2 & \cdots & n-2 & n-1 \\
|
|
|
|
|
3 & 2 & 1 & \cdots & n-3 & n-2 \\
|
|
|
|
|
@ -215,7 +215,7 @@ k= \underline{\qquad\qquad\qquad\qquad}.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
M_n =\begin{vmatrix}
|
|
|
|
|
1+x_1 & 1+x_1^2 & \cdots & 1+x_1^n \\
|
|
|
|
|
1+x_2 & 1+x_2^2 & \cdots & 1+x_2^n \\
|
|
|
|
|
\vdots & \vdots & \ddots & \vdots \\
|
|
|
|
|
@ -223,9 +223,167 @@ $$
|
|
|
|
|
\end{vmatrix}
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
---
|
|
|
|
|
|
|
|
|
|
13. 设$A=\begin{bmatrix}1 & -1 & 0 & -1 \\ 1 & 1 & 0 & 3 \\ 2 & 1 & 2 & 6\end{bmatrix},B=\begin{bmatrix}1 & 0 & 1 & 2 \\ 1 & -1 & a & a-1 \\ 2 & -3 & 2 & -2\end{bmatrix}$,向量$\alpha=\begin{bmatrix}0\\2\\3\end{bmatrix},\beta=\begin{bmatrix}1\\0\\-1\end{bmatrix}$.
|
|
|
|
|
解析
|
|
|
|
|
(1)$K_n$:
|
|
|
|
|
从第 $n-1$ 行开始,依次乘以 $(-1)$ 加到下一行,再把第 $n$ 列加到前面各列,得
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
\begin{aligned}
|
|
|
|
|
K_n &=
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
1 & 2 & 3 & \cdots & n-1 & n \\
|
|
|
|
|
2 & 1 & 2 & \cdots & n-2 & n-1 \\
|
|
|
|
|
3 & 2 & 1 & \cdots & n-3 & n-2 \\
|
|
|
|
|
\vdots & \vdots & \vdots & \ddots & \vdots & \vdots \\
|
|
|
|
|
n-1 & n-2 & n-3 & \cdots & 1 & 2 \\
|
|
|
|
|
n & n-1 & n-2 & \cdots & 2 & 1
|
|
|
|
|
\end{vmatrix} \\[4pt]
|
|
|
|
|
&=
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
1 & 2 & 3 & \cdots & n-1 & n \\
|
|
|
|
|
1 & -1 & -1 & \cdots & -1 & -1 \\
|
|
|
|
|
1 & 1 & -1 & \cdots & -1 & -1 \\
|
|
|
|
|
\vdots & \vdots & \vdots & \ddots & \vdots & \vdots \\
|
|
|
|
|
1 & 1 & 1 & \cdots & -1 & -1 \\
|
|
|
|
|
1 & 1 & 1 & \cdots & 1 & -1
|
|
|
|
|
\end{vmatrix}
|
|
|
|
|
|
|
|
|
|
\end{aligned}
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
继续化简:
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
\begin{aligned}
|
|
|
|
|
&=
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
n+1 & n+2 & n+3 & \cdots & 2n-1 & n \\
|
|
|
|
|
0 & -2 & -2 & \cdots & -2 & -1 \\
|
|
|
|
|
0 & 0 & -2 & \cdots & -2 & -1 \\
|
|
|
|
|
\vdots & \vdots & \vdots & \ddots & \vdots & \vdots \\
|
|
|
|
|
0 & 0 & 0 & \cdots & -2 & -1 \\
|
|
|
|
|
0 & 0 & 0 & \cdots & 0 & -1
|
|
|
|
|
\end{vmatrix}
|
|
|
|
|
|
|
|
|
|
\end{aligned}
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
这是一个上三角行列式,因此
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
D_n = (-1)^{n-1} \cdot 2^{n-2} \cdot (n+1)
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
---
|
|
|
|
|
(2)加边
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
\tilde{D} =
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
1 & 0 & 0 & \cdots & 0 \\
|
|
|
|
|
1 & 1 + x_1 & 1 + x_1^2 & \cdots & 1 + x_1^n \\
|
|
|
|
|
1 & 1 + x_2 & 1 + x_2^2 & \cdots & 1 + x_2^n \\
|
|
|
|
|
\vdots & \vdots & \vdots & \ddots & \vdots \\
|
|
|
|
|
1 & 1 + x_n & 1 + x_n^2 & \cdots & 1 + x_n^n
|
|
|
|
|
\end{vmatrix}
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
\tilde{D} =
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
1 & -1 & -1 & \cdots & -1 \\
|
|
|
|
|
1 & x_1 & x_1^2 & \cdots & x_1^n \\
|
|
|
|
|
1 & x_2 & x_2^2 & \cdots & x_2^n \\
|
|
|
|
|
\vdots & \vdots & \vdots & \ddots & \vdots \\
|
|
|
|
|
1 & x_n & x_n^2 & \cdots & x_n^n
|
|
|
|
|
\end{vmatrix}
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
将第一行拆为 $(2,0,0,\dots,0)$ 与 $(-1,-1,\dots,-1)$ 之和:
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
\tilde{D} =
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
2 & 0 & 0 & \cdots & 0 \\
|
|
|
|
|
1 & x_1 & x_1^2 & \cdots & x_1^n \\
|
|
|
|
|
1 & x_2 & x_2^2 & \cdots & x_2^n \\
|
|
|
|
|
\vdots & \vdots & \vdots & \ddots & \vdots \\
|
|
|
|
|
1 & x_n & x_n^2 & \cdots & x_n^n
|
|
|
|
|
\end{vmatrix}
|
|
|
|
|
+
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
-1 & -1 & -1 & \cdots & -1 \\
|
|
|
|
|
1 & x_1 & x_1^2 & \cdots & x_1^n \\
|
|
|
|
|
1 & x_2 & x_2^2 & \cdots & x_2^n \\
|
|
|
|
|
\vdots & \vdots & \vdots & \ddots & \vdots \\
|
|
|
|
|
1 & x_n & x_n^2 & \cdots & x_n^n
|
|
|
|
|
\end{vmatrix}
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
令左边为 $A$,右边为 $B$。
|
|
|
|
|
|
|
|
|
|
计算 $A$,按第一行展开:
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
A = 2 \cdot
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
x_1 & x_1^2 & \cdots & x_1^n \\
|
|
|
|
|
x_2 & x_2^2 & \cdots & x_2^n \\
|
|
|
|
|
\vdots & \vdots & \ddots & \vdots \\
|
|
|
|
|
x_n & x_n^2 & \cdots & x_n^n
|
|
|
|
|
\end{vmatrix}
|
|
|
|
|
= 2 \cdot \left( \prod_{i=1}^{n} x_i \right) \cdot
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
1 & x_1 & \cdots & x_1^{n-1} \\
|
|
|
|
|
1 & x_2 & \cdots & x_2^{n-1} \\
|
|
|
|
|
\vdots & \vdots & \ddots & \vdots \\
|
|
|
|
|
1 & x_n & \cdots & x_n^{n-1}
|
|
|
|
|
\end{vmatrix}
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
右边为范德蒙德行列式:
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
A = 2 \prod_{i=1}^{n} x_i \cdot \prod_{1 \leq i < j \leq n} (x_j - x_i)
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
计算 $B$,提出第一行的因子 $-1$:
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
B = (-1) \cdot
|
|
|
|
|
\begin{vmatrix}
|
|
|
|
|
1 & 1 & 1 & \cdots & 1 \\
|
|
|
|
|
1 & x_1 & x_1^2 & \cdots & x_1^n \\
|
|
|
|
|
1 & x_2 & x_2^2 & \cdots & x_2^n \\
|
|
|
|
|
\vdots & \vdots & \vdots & \ddots & \vdots \\
|
|
|
|
|
1 & x_n & x_n^2 & \cdots & x_n^n
|
|
|
|
|
\end{vmatrix}
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
该行列式为 $n+1$ 阶范德蒙德行列式,变量为 $1, x_1, x_2, \dots, x_n$:
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
B = (-1) \cdot \prod_{i=1}^{n} (x_i - 1) \cdot \prod_{1 \leq i < j \leq n} (x_j - x_i)
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
因此:
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
\tilde{D} = A + B = \left( 2 \prod_{i=1}^{n} x_i - \prod_{i=1}^{n} (x_i - 1) \right) \cdot \prod_{1 \leq i < j \leq n} (x_j - x_i)
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
$$
|
|
|
|
|
\boxed{\tilde{D} = \left(2\prod\limits_{i=1}^{n}x_i - \prod\limits_{i=1}^{n}(x_i-1)\right) \prod\limits_{1\leq i<j\leq n}(x_j-x_i)}
|
|
|
|
|
$$
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
---
|
|
|
|
|
14. 设$A=\begin{bmatrix}1 & -1 & 0 & -1 \\ 1 & 1 & 0 & 3 \\ 2 & 1 & 2 & 6\end{bmatrix},B=\begin{bmatrix}1 & 0 & 1 & 2 \\ 1 & -1 & a & a-1 \\ 2 & -3 & 2 & -2\end{bmatrix}$,向量$\alpha=\begin{bmatrix}0\\2\\3\end{bmatrix},\beta=\begin{bmatrix}1\\0\\-1\end{bmatrix}$.
|
|
|
|
|
|
|
|
|
|
(1)证明:方程组$Ax=\alpha$的解均为方程组$Bx=\beta$的解;
|
|
|
|
|
(2)若方程组$Ax=\alpha$与方程组$Bx=\beta$不同解,求$a$的值.
|
|
|
|
|
@ -239,7 +397,7 @@ $$
|
|
|
|
|
|
|
|
|
|
---
|
|
|
|
|
|
|
|
|
|
14. (10 分)设
|
|
|
|
|
15. (10 分)设
|
|
|
|
|
$$
|
|
|
|
|
\alpha_1 = (1,0,-1)^T,\quad \alpha_2 = (2,1,1)^T,\quad \alpha_3 = (1,1,1)^T
|
|
|
|
|
$$
|
|
|
|
|
@ -315,13 +473,13 @@ $$
|
|
|
|
|
1 & 0 & 1 & \vert & -2 \\
|
|
|
|
|
0 & 1 & 1 & \vert & 1 \\
|
|
|
|
|
0 & -1 & 0 & \vert & 2
|
|
|
|
|
\end{bmatrix} \\
|
|
|
|
|
\end{bmatrix} \\[1em]
|
|
|
|
|
&\rightarrow
|
|
|
|
|
\begin{bmatrix}
|
|
|
|
|
1 & 0 & 1 & \vert & -2 \\
|
|
|
|
|
0 & 1 & 1 & \vert & 1 \\
|
|
|
|
|
0 & 0 & 1 & \vert & 3
|
|
|
|
|
\end{bmatrix} \\
|
|
|
|
|
\end{bmatrix} \\[1em]
|
|
|
|
|
&\rightarrow
|
|
|
|
|
\begin{bmatrix}
|
|
|
|
|
1 & 0 & 0 & \vert & -5 \\
|
|
|
|
|
@ -346,7 +504,7 @@ $$
|
|
|
|
|
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
15. (12 分)设 $n$ 阶方阵 $A, B$ 满足 $AB = A + B$。
|
|
|
|
|
16. (12 分)设 $n$ 阶方阵 $A, B$ 满足 $AB = A + B$。
|
|
|
|
|
|
|
|
|
|
(1)证明 $A - E$ 可逆;
|
|
|
|
|
|
|
|
|
|
@ -368,11 +526,75 @@ $$
|
|
|
|
|
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
**【解】**
|
|
|
|
|
|
|
|
|
|
**(1)**
|
|
|
|
|
由 $AB = A + B$ 得 $(A - E)(B - E) = E$,因此 $A - E$ 可逆。
|
|
|
|
|
$$\text{……3 分}$$
|
|
|
|
|
|
|
|
|
|
**(2)**
|
|
|
|
|
由 $(A - E)(B - E) = E$ 得 $(B - E)(A - E) = E$,因此 $AB = BA$。
|
|
|
|
|
$$\text{……6 分}$$
|
|
|
|
|
|
|
|
|
|
**(3)**
|
|
|
|
|
由 $AB = A + B$ 得 $A = (A - E)B$,而 $A - E$ 可逆,故
|
|
|
|
|
$$
|
|
|
|
|
\mathrm{rank}(A) = \mathrm{rank}(B).
|
|
|
|
|
$$
|
|
|
|
|
$$\text{……9 分}$$
|
|
|
|
|
|
|
|
|
|
**(4)**
|
|
|
|
|
由 $AB = A + B$ 得 $A(B - E) = B$,而 $B - E$ 可逆,故
|
|
|
|
|
$$
|
|
|
|
|
A = B(B - E)^{-1}.
|
|
|
|
|
$$
|
|
|
|
|
已知
|
|
|
|
|
$$
|
|
|
|
|
B = \begin{bmatrix}
|
|
|
|
|
1 & -3 & 0 \\
|
|
|
|
|
2 & 1 & 0 \\
|
|
|
|
|
0 & 0 & 2
|
|
|
|
|
\end{bmatrix},
|
|
|
|
|
$$
|
|
|
|
|
则
|
|
|
|
|
$$
|
|
|
|
|
B - E = \begin{bmatrix}
|
|
|
|
|
0 & -3 & 0 \\
|
|
|
|
|
2 & 0 & 0 \\
|
|
|
|
|
0 & 0 & 1
|
|
|
|
|
\end{bmatrix}.
|
|
|
|
|
$$
|
|
|
|
|
求逆得
|
|
|
|
|
$$
|
|
|
|
|
(B - E)^{-1} = \begin{bmatrix}
|
|
|
|
|
0 & \frac12 & 0 \\[2pt]
|
|
|
|
|
-\frac13 & 0 & 0 \\[2pt]
|
|
|
|
|
0 & 0 & 1
|
|
|
|
|
\end{bmatrix}.
|
|
|
|
|
$$
|
|
|
|
|
于是
|
|
|
|
|
$$
|
|
|
|
|
A = B(B - E)^{-1} = \begin{bmatrix}
|
|
|
|
|
1 & -3 & 0 \\
|
|
|
|
|
2 & 1 & 0 \\
|
|
|
|
|
0 & 0 & 2
|
|
|
|
|
\end{bmatrix}
|
|
|
|
|
\begin{bmatrix}
|
|
|
|
|
0 & \frac12 & 0 \\[2pt]
|
|
|
|
|
-\frac13 & 0 & 0 \\[2pt]
|
|
|
|
|
0 & 0 & 1
|
|
|
|
|
\end{bmatrix}
|
|
|
|
|
= \begin{bmatrix}
|
|
|
|
|
1 & \frac12 & 0 \\[2pt]
|
|
|
|
|
-\frac13 & 1 & 0 \\[2pt]
|
|
|
|
|
0 & 0 & 2
|
|
|
|
|
\end{bmatrix}.
|
|
|
|
|
$$
|
|
|
|
|
$$\text{……12 分}$$
|
|
|
|
|
|
|
|
|
|
---
|
|
|
|
|
|
|
|
|
|
16. 设矩阵$A=\begin{bmatrix}1&2&1&2\\0&1&t&t\\1&t&0&1\end{bmatrix}$,齐次线性方程组Ax=0的基础解系中含有两个解向量,求Ax=0的通解。
|
|
|
|
|
17. 设矩阵$A=\begin{bmatrix}1&2&1&2\\0&1&t&t\\1&t&0&1\end{bmatrix}$,齐次线性方程组Ax=0的基础解系中含有两个解向量,求Ax=0的通解。
|
|
|
|
|
|
|
|
|
|
---
|
|
|
|
|
|
|
|
|
|
|