线性代数 · 免费预览

特征值与特征向量

特征值与特征向量

1. Eigenvalues and Eigenvectors

Eigenvalues and Eigenvectors

2. Introduction

Introduction

3. Eigenvalues and Eigenvectors

Eigenvalues and Eigenvectors

4. Eigenspaces

Eigenspaces

5. The Invertible Matrix Theorem: Addenda

The Invertible Matrix Theorem: Addenda

6. Spot the eigenvector

Let A=(22−48)A = \begin{pmatrix} 2 & 2 \\ -4 & 8 \end{pmatrix}. Which of the following is an eigenvector of AA?

7. Eigenvalue equal to zero

Let A=(1326)A = \begin{pmatrix} 1 & 3 \\ 2 & 6 \end{pmatrix}. Which statement is true?

8. Vocabulary: eigenvalue

If Av=λvAv = \lambda v for some nonzero vector vv, then the scalar λ\lambda is called an ______ of AA.

9. Eigenvalue of a reflection

Let A=(0110)A = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix} (reflection across the line y=xy=x) and v=(3−3)v = \begin{pmatrix} 3 \\ -3 \end{pmatrix}. Compute AvAv and enter the eigenvalue of AA for this eigenvector (a number).

10. Rank from eigenvalues

A 3×33\times3 matrix BB is known to have eigenvalues 00, 11 and 22. Enter the rank of BB (a number).

11. What an eigenspace is

Let λ\lambda be an eigenvalue of a square matrix AA. The eigenspace of AA corresponding to λ\lambda is defined as which set?

12. A basis vector of an eigenspace

Let A=(2103)A = \begin{pmatrix} 2 & 1 \\ 0 & 3 \end{pmatrix}. The number λ=2\lambda = 2 is an eigenvalue. Enter a basis vector of the eigenspace as x,yx,y.

进入交互式练习

免费注册 · 即时批改 · 自动安排间隔复习。

免费开始这门课