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School of Engineering
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- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
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School of Environment and Society
- Department of Architecture and Building Engineering
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- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Graduate major in Systems and Control Engineering
- Instructor(s)
- Hara Seiichiro
- Class Format
- Lecture
- Media-enhanced courses
- Day/Period(Room No.)
- Tue5-6(W321)
- Group
- -
- Course number
- SCE.I401
- Credits
- 1
- Academic year
- 2019
- Offered quarter
- 1Q
- Syllabus updated
- 2019/3/18
- Lecture notes updated
- -
- Language used
- English
- Access Index
-
Course description and aims
This course starts off discussing concepts and applications of the measurement of physical phenomena and the processing of measured signals. Next spectral analysis and filtering are discussed as examples of processing linear signals. Next, statistical signal processing and adaptive signal processing are discussed as examples of nonlinear signal processing. Finally, analysis methods for analyzing and evaluating signals are discussed. To make machines and systems move in tune with their surrounding environment, it is necessary to obtain and evaluate necessary information from physical phenomena. The goal of this course is for students, as a first step, to acquire the knowledge and technology to measure and analyze phenomena.
Student learning outcomes
By the end of this course, students will learn the following:
1) Understanding of the measurement and digitization of the information in a phenomenon.
2) Understanding of the basic and advanced processing of time series signal.
3) Skills to apply the knowledge listed above.
Keywords
Measurement, Signal processing, Digital signal processing, Spectrum analysis
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
Class flow
Lectures and simple exercises will be given.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Concepts and application of the measurement and processing of the signals | Reports on signal processing in students' research fields |
| Class 2 | Spectrum analysis (Fourier analysis, MEM spectrum) | Report on spectrum analysis |
| Class 3 | Linear filtering | Report on linear filtering |
| Class 4 | 2D filtering, Noise filtering, correlation function | Report on correlation function |
| Class 5 | Fractal and wavelet analysis | Report on wavelet analysis |
| Class 6 | Parameterization and analysis of statistical parameters | Report on statistical parameters |
| Class 7 | Correction of Waveform Distortion | Report on Waveform Distortion |
| Class 8 | Summary | None |
Textbook(s)
Course materials are provided during class.
Reference books, course materials, etc.
Random Data: Analysis and Measurement Procedures, Julius S. Bendat & Allan G. Piersol, 4th edition, 1998
Chaotic and Fractal Dynamics: An Introduction for Applied Scientists and Engineers, Francis C. Moon, 1992
Assessment criteria and methods
Students will be assessed by their understanding of the ideas discussed in the lectures and their abilities to apply them to reports and the final reports.
Related courses
- SCE.I303 ： Sensing Systems Theory
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Not required
