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2021 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)
5-6 Mon (S421,S422) / 5-6 Thu (S421,S422)
Class
-
Course Code
SCE.M203
Number of credits
200
Course offered
2021
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

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)

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.