| Course title | |||||
| 線形代数学Ⅱ [Linear Algebra Ⅱ] | |||||
| Course category | technology speciality courses,ets. | Requirement | Credit | 2 | |
| Department | Year | 1～4 | Semester | Fall | |
| Course type | Fall | Course code | 021609 | ||
| Instructor(s) | |||||
| 澤田 伸晴 [SAWADA Nobuharu] | |||||
| Facility affiliation | Graduate School of Engineering | Office | Email address | ||
| Course description |
| In this course, the notion of a vector space and a linear map between two vector spaces will be introduced. We will learn various basic properties of a basis and the dimension of a vector space, and the image and the kernel of a linear map. We will also learn about an eigenvalue and an eigenvector, for deep understanding of linear algebra. |
| Expected Learning |
|
The goals of this course are (1) to understand vector spaces, linear maps, eigenvalues, eigenvectors, inner products and diagonalization, and (2) to be capable of performing their practical calculations. |
| Course schedule |
|
1. Vector spaces 2. Vector spaces and their subspaces 3. Linear independence and linear dependence 4. Maximum of linearly independent vectors 5. Bases and dimensions of vector spaces 6. Linear maps 7. Representation matrices of linear maps 8. Exercises, or midterm examination 9. Eigenvalues and eigenvectors 10. Diagonalization of square matrices 11. Inner products and complex numbers 12. Orthonormalization and orthogonal matrices 13. Diagonalization of real symmetric matrices 14. Cayley-Hamilton theorem 15. Term examination |
| Prerequisites |
| Knowledge of the course of Linear Algebra I will be used in the lecture. |
| Required Text(s) and Materials |
| References |
|
MIYAKE, Toshitsune, “Nyuumon-Senkei-Daisuu”, Baifu-kan (in Jananese), SAITO, Masahiko, “Senkei-Daisuu-Nyuumon”, Tokyo Daigaku shuppan-kai (in Japanese), SATAKE, Ichiro, “Senkei-Daisuugaku”, Shoukabou (in Japanese). |
| Assessment/Grading |
| Exercises or Midterm exam (50%), Term exam (50%) |
| Message from instructor(s) |
| Course keywords |
| vector space, linear map, linear independence, basis, dimension, eigenvalue, eigenspace, diagonalization |
| Office hours |
| Remarks 1 |
| Remarks 2 |
| Related URL |
| Lecture Language |
| Language Subject |
| Last update |
| 9/29/2017 8:36:08 AM |