Hiroshima University Syllabus

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Academic Year 2022Year School/Graduate School School of Informatics and Data Science
Lecture Code KA121001 Subject Classification Specialized Education
Subject Name フーリエ解析
Subject Name
Subject Name in
Fourier Analysis
アイザワ ヒロアキ
Campus Higashi-Hiroshima Semester/Term 2nd-Year,  First Semester,  2Term
Days, Periods, and Classrooms (2T) Mon9-10,Thur7-8:ENG 220
Lesson Style Lecture Lesson Style
(More Details)
Credits 2.0 Class Hours/Week   Language of Instruction B : Japanese/English
Course Level 2 : Undergraduate Low-Intermediate
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 01 : Mathematics/Statistics
Eligible Students
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
In this course, students are expected to learn Fourier analysis as a basis for processing signals such as images and sounds, and to develop the ability to create programs to realize them.  
Criterion referenced
Informatics and Data Science Program
(Knowledge and Understanding)
・I1. Knowledge and ability required for collecting and processing high-dimensional data using information processing technologies based on scientific logic, while understanding the theoretical system that forms the basis of informatics.
Class Objectives
/Class Outline
To understand Fourier analysis as the basis of signal processing, and to acquire the knowledge and ability to create programs to analyze signals for voice, images, etc. 
Class Schedule Lesson 1.  Introduction to Fourier Analysis
Lesson 2. Least Squares Method
Lesson 3. Orthogonal function expansion

Lesson 4. Inner product spaces
Lesson 5. Fourier series expansion

Lesson 6. Complex Fourier Series Expansion

Lesson 7. Fourier Transform

Lesson 8. Convolution Theorem
Lesson 9. Sampling Theorem
Lesson 10. Discrete Fourier Transform
Lesson 11. Fourier Analysis and Principal Axis Transform
Lesson 12. Wavelet Analysis
Lesson 13. Laplace Transform
Lesson 14. Fourier Analysis and Differential Equation
Lesson 15. Summary and Discussion 
Reference Book: A. Boggess, F.J. Narcowich, A First Course in Wavelets with Fourier Analysis 
PC or AV used in
(More Details) Slides 
Learning techniques to be incorporated  
Suggestions on
Preparation and
It will be easier to understand if you study the textbook beforehand. In addition, it will be easier to understand if you actually run the program. 
Grading Method Evaluation will be based on reports. 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. 
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