Course title
線形代数学Ⅰ   [Linear Algebra Ⅰ]
Course category technology speciality courses  Requirement   Credit 2 
Department Department of Electrical Engineering and Computer Science, Electrical and Electronic Engineering(~2018), Computer and Information Sciences(~2018)  Year 14  Semester 1st 
Course type 1st  Course code 021907
Instructor(s)
堀口 直之   [HORIGUCHI Naoyuki]
Facility affiliation Graduate School of Engineering Office   Email address

Course description
Linear algebra provides indispensable tools to analyze various mathematical phenomena appearing in engineering. In this course, we will learn various computations based on matrices so that we can treat more abstract notions such as vector spaces at hand.
Expected Learning
・To be able to solve simultaneous equations by using elementary transformation of matrices.
・To be able to understand and calculate determinants of matrices.
Corresponding criteria in the Diploma Policy: See the Curriculum maps

Course schedule
1. Definition and operations of matrices
2. Zero matrix, identity matrix and exponentiations of matrices
3. Transpose of matrices
4. Regular matrices and block matrices
5. Elementary transformations and ranks of matrices
6. Solution of simultaneous linear equations
7. Homogeneous equations
8. Calculations of inverse matrices
9. Definition of ranks of matrices
10. Definition of determinants of matrices
11. Properties of determinants
12. Calculations of determinants
13. Cofactor expansion
14. Linear transformation
15. Review, and examination

Prerequisites
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
“Kyouyou no senkei daisuu”, Baifu-kan
References
Assessment/Grading
40% for short test in each class, and 60% for the examination
Message from instructor(s)
Course keywords
Matrix, Rank, System of linear equations, Determinant, Inverse matrix
Office hours
Remarks 1
Remarks 2
Related URL
Lecture Language
Japanese
Language Subject
Last update
1/29/2020 5:21:10 PM