2025 (Current Year) 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
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - Class
- -
- Course Code
- SCE.M203
- Number of credits
- 200
- Course offered
- 2025
- Offered quarter
- 4Q
- Syllabus updated
- Apr 1, 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, linear discrete-time system, transfer function, IIR system, FIR system, filter, discrete Fourier transform, coding method
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
At the end of each class, exercises will be conducted to check understanding.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Outline of lecture, basic of signal processing | Exercise on S / N ratio |
| 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 | Sampling theorem, Transfer function | Exercise on sampling theorem |
| Class 6 | IIR, FIR | 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 | Analog filter | Exercise on Digital IIR filter |
| Class 10 | Digital IIR filter | Exercise on Digital FIR filter |
| Class 11 | Digital FIR filter | Exercise on Adaptive signal processing |
| Class 12 | Adaptive signal processing | Exercise on Adaptive signal processing |
| Class 13 | Coding of the signal (waveform coding) | Exercise on Coding of the signal |
| Class 14 | Coding of the signal (vector quantization) | none |
| 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)
Lecture materials will be distributed at LMS.
Reference books, course materials, etc.
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.