Course title
線形代数学Ⅱ   [Linear Algebra Ⅱ]
Course category technology speciality courses  Requirement   Credit 2 
Department Department of Applied Chemistry, Applied Chemistry(~2018), Organic and Polymer Materials Chemistry(~2018)  Year 14  Semester 3rd 
Course type 3rd  Course code 021919
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.

Nobuharu Sawada (a part time lecturer) will be in charge of this course.
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.

Corresponding criteria in the Diploma Policy: See the Curriculum maps.
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. Review, and Term examination
Prerequisites
Knowledge of the course of Linear Algebra I will be used in the lecture.
In addition to 30 hours that students spend in the class, students are recommended to prepare for and revise the lectures, spending the standard amount of time as specified by the University and using the lecture handouts as well as the references specified below.
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
5/31/2019 4:17:16 PM