2024 Faculty Courses Liberal arts and basic science courses Basic science and technology courses
Linear Algebra II Q(41～50)
- Academic unit or major
- Basic science and technology courses
- Instructor(s)
- Satoshi Naito
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 1-2 Mon / 3-4 Fri
- Class
- Q(41～50)
- Course Code
- LAS.M106
- Number of credits
- 200
- Course offered
- 2024
- Offered quarter
- 4Q
- Syllabus updated
- Mar 14, 2025
- Language
- Japanese
Syllabus
Course overview and goals
Building on the content of "Linear Algebra I", the instructor will explain the fundamentals of vector spaces and linear mapping, eigenvalues and diagonalization, and the inner product of vector spaces.
The aim of this course is to explain the theory of vector spaces which will be important for science and engineering.
Course description and aims
This course follows "Linear Algebra I: Exercise". Students will acquire the fundamentals of linear algebra. They will also deepen and further develop their understanding of content learned in "Linear Algebra I".
Keywords
Vector space, basis, linear transformation, eigenvalue, diagonalization
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Aside from the lecture, exercises will be done once a week in tune with the progress of the lecture.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Vector space, subspace | Understand basics of vector spaces. |
| Class 2 | Linear combination, linear independence, linear dependence | Understand linear independence and related notions. |
| Class 3 | Basis, dimension | Understand basis and dimension of vector spaces. |
| Class 4 | Existence of basis | Understand a proof of the existence of a basis. |
| Class 5 | Linear transformation, kernel and image | Understand linear transformation and related notions. |
| Class 6 | Representation matrix of linear transformation | Understand the representation matrix of linear transformation. |
| Class 7 | Inner product and norm, Schwarz's inequality | Understand the definition and properties of inner product and norm. |
| Class 8 | Orthonormal basis, orthogonalization method of Schmitt | Understand orthogonality and related notions. |
| Class 9 | Coordinate transformation, orthogonal matrix, unitary matrix | Understand coordinate transformation and related notions. |
| Class 10 | Eigenvalue, eigenvector | Understand the definition of an eigenvalue and an eigenvector. |
| Class 11 | Characteristic polynomial, multiplicity, eigenspace | Understand the properties of eigenvalues. |
| Class 12 | Triangularization and diagonalization of matrices | Understand the triangularization and diagonalization of matrices. |
| Class 13 | Diagonalization of normal matrices, diagonalization real symmetric matrix | Understand notions related to diagonalization. |
| Class 14 | Advance topics | Understand advanced topics in Linear Algebra. |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
Linear Algebra for Engineering , Mitsutaka Murayama, Suurikougakusha
Reference books, course materials, etc.
None in particular.
Evaluation methods and criteria
Based on overall evaluation on the results of quizzes, reports, mid-term and final examinations. Details will be announced in class.
Related courses
- LAS.M102 ： Linear Algebra I / Recitation
- LAS.M108 ： Linear Algebra Recitation II
Prerequisites
Students are supposed to have completed Linear Algebra I / Recitation (LAS.M102).
Students are recommended to take Linear Algebra Recitation II (LAS.M108) at the same time.