2008年考研数学二第23题
📝 题目
设 $\boldsymbol{A}$ 为3阶矩阵, $\boldsymbol{\alpha}_{1}, \boldsymbol{\alpha}_{2}$ 为 $\boldsymbol{A}$ 的分别属于特征值 $-1,1$ 的特征向量,向量 $\boldsymbol{\alpha}_{3}$ 满足 $A\alpha_{3}= {\alpha}_{2}+{\alpha}_{3}$. (I)证明 $\boldsymbol{\alpha}_{1}, \boldsymbol{\alpha}_{2}, \boldsymbol{\alpha}_{3}$ 线性无关; (II)令 $\boldsymbol{P}=\left(\boldsymbol{\alpha}_{1}, \boldsymbol{\alpha}_{2}, \boldsymbol{\alpha}_{3}\right)$ ,求 $\boldsymbol{P}^{-1} \boldsymbol{A P}$ .
💡 答案解析
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(23)【详解】(I) 证法一:假设 $\alpha_1, \alpha_2, \alpha_3$ 线性相关.因为 $\alpha_1, \alpha_2$ 分别属于不同特征值的特征向量,故 $\alpha_1, \alpha_2$ 线性无关,则 $\alpha_3$ 可由 $\alpha_1, \alpha_2$ 线性表出,不妨设 $\alpha_3=l_1 \alpha_1+l_2 \alpha_2$ ,其中 $l_1, l_2$ 不全为零(若 $l_1, l_2$ 同时为 0 ,则 $\alpha_3$ 为 0 ,由 $A \alpha_3=\alpha_2+\alpha_3$ 可知 $\alpha_2=0$ ,而特征向量都是非 0 向量,矛盾)
$$ \begin{aligned} & \because A \alpha_1=-\alpha_1, A \alpha_2=\alpha_2 \\ & \therefore A \alpha_3=\alpha_2+\alpha_3=\alpha_2+l_1 \alpha_1+l_2 \alpha_2, \text { 又 } A \alpha_3=A\left(l_1 \alpha_1+l_2 \alpha_2\right)=-l_1 \alpha_1+l_2 \alpha_2 \\ & \therefore-l_1 \alpha_1+l_2 \alpha_2=\alpha_2+l_1 \alpha_1+l_2 \alpha_2, \text { 整理得: } 2 l_1 \alpha_1+\alpha_2=0 \end{aligned} $$
则 $\alpha_1, \alpha_2$ 线性相关,矛盾.所以,$\alpha_1, \alpha_2, \alpha_3$ 线性无关.
证法二:设存在数 $k_1, k_2, k_3$ ,使得 $k_1 \alpha_1+k_2 \alpha_2+k_3 \alpha_3=0$ (1)
用 $A$ 左乘(1)的两边并由 $A \alpha_1=-\alpha_1, A \alpha_2=\alpha_2$ 得
$$ \begin{array}{ll} & -k_1 \alpha_1+\left(k_2+k_3\right) \alpha_2+k_3 \alpha_3=0 \qquad(2)\\ (1)-(2) \text { 得 } & 2 k_1 \alpha_1-k_3 \alpha_2=0 \qquad(3) \end{array} $$
因为 $\alpha_1, \alpha_2$ 是 $A$ 的属于不同特征值的特征向量,所以 $\alpha_1, \alpha_2$ 线性无关,从而 $k_1=k_3=0$ ,代入(1)得 $k_2 \alpha_2=0$ ,又由于 $\alpha_2 \neq 0$ ,所以 $k_2=0$ ,故 $\alpha_1, \alpha_2, \alpha_3$ 线性无关. (II)记 $P=\left(\alpha_1, \alpha_2, \alpha_3\right)$ ,则 $P$ 可逆, $$ \begin{aligned} A P & =A\left(\alpha_1, \alpha_2, \alpha_3\right)=\left(A \alpha_1, A \alpha_2, A \alpha_3\right)=\left(-\alpha_1, \alpha_2, \alpha_2+\alpha_3\right) \\ & =\left(\alpha_1, \alpha_2, \alpha_3\right)\left(\begin{array}{ccc} -1 & 0 & 0 \\ 0 & 1 & 1 \\ 0 & 0 & 1 \end{array}\right)=P\left(\begin{array}{ccc} -1 & 0 & 0 \\ 0 & 1 & 1 \\ 0 & 0 & 1 \end{array}\right) \\ & P^{-1} A P=\left(\begin{array}{ccc} -1 & 0 & 0 \\ 0 & 1 & 1 \\ 0 & 0 & 1 \end{array}\right) . \end{aligned} $$