2020 Faculty Courses School of Engineering Undergraduate major in Systems and Control Engineering
Digital Signal Processing
- Academic unit or major
- Undergraduate major in Systems and Control Engineering
- Instructor(s)
- Seiichiro Hara
- Class Format
- Lecture (Zoom)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 5-6 Mon (S422) / 5-6 Thu (S422)
- Class
- -
- Course Code
- SCE.I203
- Number of credits
- 200
- Course offered
- 2020
- Offered quarter
- 4Q
- Syllabus updated
- Jul 10, 2025
- Language
- Japanese
Syllabus
Course overview and goals
The instructor lectures on the digitization of signal and orthogonal transforms including the Discrete Fourier transform for connecting a time and frequency domains.
The instructor lectures on the coding method of time-series signal including examples.
In addition, the instructor lectures on the theory and design FIR of IIR filters based on linear discrete-time systems.
For the analysis or development of a machine or system adapting to the conditions of the surrounding environment or itself, knowledge on and skills for analyzing the measured information are essential.
The instructor in this course lectures on the signal processing technique that is enabled by digitization.
As its first step, this course facilitates students' knowledge and skills about measurement and analysis of the phenomenon.
Course description and aims
At the end of this course, students will be able to:
1) Understand the concept of digitization of time series signal
2) Understand the processing technique applied to digital signal such as filtering and Fourier transform
3) Gain the skill to apply the method listed above
The processing is understood to be applied to the digitization of concepts and digitized signals relating to one-dimensional signals, and a target to be able to acquire practiced technology.
Keywords
Quantization, discretization, digitization, discrete Fourier transform, coding, linear discrete-time system theory, filter
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Lectures and practice exercises will be given.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Outline of lecture, basic of signal processing | None |
| Class 2 | Linear time invariant system, convolution | Exercise on convolution |
| Class 3 | Z conversion | Exercise on Z conversion |
| Class 4 | Discrete Fourier Transform | Exercise on Fourier Transform |
| Class 5 | Discrete-time system, sampling theorem | Exercise on sampling theorem |
| Class 6 | Transfer function, Impulse response | Exercise on Transfer function, Impulse response |
| Class 7 | Frequency characteristics, system stability | Exercise on Frequency characteristics, system stability |
| Class 8 | Fast Fourier Transform | Exercise on Fast Fourier Transform |
| Class 9 | Digital IIR filter | Exercise on Digital IIR filter |
| Class 10 | Digital FIR filter | Exercise on Digital FIR filter |
| Class 11 | Adaptive signal processing | Exercise on Adaptive signal processing |
| Class 12 | Coding of the signal (waveform coding, vector quantization) | Exercise on coding |
| Class 13 | Autocorrelation function | Exercise on Autocorrelation function |
| Class 14 | Estimation of power spectrum | Exercise on Estimation of power spectrum |
| Class 15 | Summary and final exam | none |
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)
None required.
Reference books, course materials, etc.
Lecture materials will be distributed in each class.
Reference books
ディジタル信号処理: 大類重範, 日本理工出版会(2001)
スペクトル解析: 日野 幹雄, 朝倉書店(1977)
Evaluation methods and criteria
Understanding of the course content is evaluated by each exercise and final test.
Related courses
- SCE.I201 ： Introduction to Measurement Engineering
- SCE.I202 ： Random Signal Processing
- SCE.I301 ： Image Sensing
Prerequisites
Enrollment in the "Introduction to Measurement Engineering" and "Random Signal Processing" is desirable.