作业 0922

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9/22 作业

Homework 4

  1. (1) 33 , 11 , 22 .

    (2) 22 , 22 , 相同。

    (3) 33 .

  2. 14\mathbf 1_4 , (100010001000000)\begin{pmatrix}1 & 0 & 0\\ 0 & 1 & 0\\ 0 & 0 & 1\\ 0 & 0 & 0\\ 0 & 0 & 0\end{pmatrix} .

  3. (a) diag⁡(25,0,−19)\operatorname{diag}( \frac{2}{5}, 0, -\frac{1}{9} ) .

    (b) (1123000121213)\begin{pmatrix}1 & 1 & \frac{2}{3}\\ 0 & 0 & 0\\ \frac{1}{2} & \frac{1}{2} & \frac{1}{3}\end{pmatrix} .

    (c) (851103100−19)\begin{pmatrix}\frac{8}{5} & 1 & 1\\ 0 & 3 & 1\\ 0 & 0 & -\frac{1}{9} \end{pmatrix} .

    (d) (112311891179)\begin{pmatrix}1 & 1 & \frac{2}{3}\\ 1 & 1 & \frac{8}{9}\\ 1 & 1 & \frac{7}{9}\end{pmatrix} .

  4. (a) 13\mathbf 1_3 because rank of the coefficient matrix is 33 .

    (b) Unique because AA is invertible.

    (c) 00 or 11 .

    rank⁡(A)=rank⁡(A∣b⃗)=3\operatorname{rank}(A) = \operatorname{rank}(A | \vec b)=3 since Ax⃗=b⃗A \vec x = \vec b has unique solution.

    rank⁡(A∣c⃗)=3\operatorname{rank}(A | \vec c) = 3 or 44 , then rank⁡(A)≤rank⁡(A∣c⃗)\operatorname{rank}(A) \le \operatorname{rank}(A | \vec c) , and the system has either one or no solution.

  5. (a) Infinitely many.

    Because rank⁡(A)=n\operatorname{rank}(A)=n , AA has right inverse.

    Therefore AA+=1nAA^+ = \mathbf 1_n .

    Lemma 1 ∀X:Rm×n\forall X : \R^{m \times n} , A(A++(1m−A+A)X)=1nA (A^+ + (\mathbf 1_m - A^+A)X) = \mathbf 1_n .

    Proof

    A(A++(1m−A+A)X)=AA++A(1m−A+A)X=1n+(A−AA+A)X=1n+(A−A)X=1n\begin{align*} A (A^+ + (\mathbf 1_m - A^+ A) X) \\ & = A A^+ + A (\mathbf 1_m - A^+ A) X \\ & = \mathbf 1_n + (A - A A^+ A) X \\ & = \mathbf 1_n + (A - A) X \\ & = \mathbf 1_n \end{align*}

    □\square .

    By lemma 1, obviously there are infinitely many right inverse of AA .

    (b) Only A−1A^{-1} .

Optional

  1. a. x⃗=0\vec x = \mathbf 0 is a solution.

    b. rank⁡(A)=rank⁡(A∣0⃗)<number of variables\operatorname{rank}(A) = \operatorname{rank}(A|\vec 0) \lt \text{number of variables} .

    c. A(x⃗1+x⃗2)=Ax⃗1+Ax⃗2=0⃗A (\vec x_1 + \vec x_2) = A \vec x_1 + A \vec x_2 = \vec 0 .

    d. A(kx⃗)=k(Ax⃗)=0⃗A(k \vec x) = k(A \vec x) = \vec 0 .

  2. a. A(x⃗1+x⃗h)=Ax⃗1+Ax⃗h=b⃗+0⃗=b⃗A (\vec x_1 + \vec x_h) = A \vec x_1 + A \vec x_h = \vec b + \vec 0 = \vec b .

    b. A(x⃗2−x⃗1)=Ax⃗2−Ax⃗1=b⃗−b⃗=0⃗A (\vec x_2 - \vec x_1) = A \vec x_2 - A \vec x_1 = \vec b - \vec b = \vec 0 .

    c. Plot.

    Plot

  3. (1)(2) 证明

    不妨令 A:Rn×nA : \R ^{n \times n} 是上三角矩阵。

    (Ak)i,i=(Ai,i)k(A^k)_{i,i} = (A_{i,i})^k , Ak=0  ⟹  Ai,i=0 ∀iA^k = \mathbf 0 \implies A_{i,i} = 0 \space \forall i .

    展开 AnA^n

    (An)i,j=∑i1,i2,⋯ ,in−1Ai,i1Ai1,i2⋯Ain−1,j\begin{equation} (A^n)_{i, j} = \sum_{i_1, i_2, \cdots, i_{n-1}} A_{i, i_1} A_{i_1, i_2} \cdots A_{i_{n-1}, j} \end{equation}

    如果 AA 的主对角线均为 00 , 由于 AA 是上三角矩阵

    Ai,j≠0  ⟹  i<jA_{i, j} \ne 0 \implies i < j

    由于 i,j:N∗≤ni,j : \N^* \le n , 不可能找到连续上升的 n+1n + 1 个下标 i,i1,i2,⋯ ,ji, i_1, i_2, \cdots, j . 故至少一项 Aik,ik+1=0A_{i_k, i_{k+1}} = 0 . 因此求和 (1) 的每一项均为 00 , (An)i,j=0(A^n)_{i, j} = 0 , An=0n×nA^n = \mathbf 0_{n \times n} □\square .

    (3) 证明 (Ak)n=0n×n(A^k)^n = \mathbf 0_{n \times n} □\square .

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