Signal Processing Engineering

Course Information

College	Anan College	Year	2024
Course Title	Signal Processing Engineering
Course Code	5397I03	Course Category	Specialized / Elective
Class Format	Lecture	Credits	Academic Credit: 2
Department	Course of Electronics and Information Engineering	Student Grade	Adv. 2nd
Term	First Semester	Classes per Week	前期:2
Textbook and/or Teaching Materials	信号処理入門（オーム社）
Instructor	Yasuno Emiko

Course Objectives

1. Understand and explain the basics of analog and digital signals.
2. Understand the definition of correlation function and be able to perform simple calculations.
3. Understand the basics of Fourier series expansion and be able to perform Fourier series expansion of basic functions.
4. Understand and explain the definition of Fourier transform.

Rubric

	Ideal Level	Standard Level	Minimum Level
Achievement 1	Able to explain analog and digital signals and apply them to practical problems.	Able to explain analog and digital signals.	Understand and explain the basics of analog and digital signals.
Achievement 2	Understand the definition of correlation functions, be able to perform simple calculations, and apply them to problem solving.	Understand the definition of correlation functions and be able to calculate them.	Understand the definition of correlation functions and be able to perform simple calculations.
Achievement 3	Understand Fourier series expansion and be able to perform Fourier series expansion.	Understand Fourier series expansion and be able to perform Fourier series expansion of basic functions.	Understand the basics of Fourier series expansion and be able to perform Fourier series expansion of basic functions.
Achievement 4	Understand the definition of Fourier transform and apply it to problem solving.	Understand and explain the definition of Fourier transform.	Explain the definition of Fourier transform.

Assigned Department Objectives

B-4 （情報技術に関する知識を応用して問題解決を遂行できる。）

Teaching Method

Outline:

There are many natural phenomena that fluctuate irregularly. The objective of this lecture is to master basic signal processing techniques for analyzing and extracting the nature of the signals buried in them.

Style:

Classes are conducted in a lecture format.
31 hours of class time + 60 hours of self-study
In order to understand the lectures and to obtain the credit, it is required to attend every class after self-studying 2 hours for preparation and 2 hours for review.

Notice:

Students are expected to not only attend lectures but also actively engage in reports and other exercises.

Course Plan

			Theme	Goals
1st Semester
	1st Quarter
		1st	What is Signal Processing? Types of Signals Analog and Digital Signals Sampling Problem	Able to explain analog and digital signals
		2nd	Examples of Signal Processing Waveform smoothing Noise compression	Able to explain waveform smoothing and noise compression
		3rd	Math Preparation Representation of signals	Understand the orthonormal basis correctly and be able to find their values by calculation
		4th	From multidimensional vector space to function space	Understand the extension from multidimensional vector spaces to function spaces
		5th	Orthonormal system	Understand the orthonormal function form correctly and be able to find the value by calculation
		6th	Correlation Functions Similarity of orthonormal functions Cross-correlation functions	Understand the cross-correlation function correctly and be able to obtain its value by calculation
		7th	Autocorrelation function	Understand the autocorrelation function correctly and be able to obtain its value by calculation
		8th	Exercises	Able to solve exercises
	2nd Quarter
		9th	Midterm examination
		10th	Fourier Series Expansion What is Fourier Series Expansion?	Understand Fourier series expansion and be able to expand a given expression
		11th	Even functions and odd functions When the period is not 2π	Able to explain even functions and odd functions
		12th	Derive complex Fourier series expansion	Derive complex Fourier series expansions
		13th	Examples of Fourier Series Expansion Percival's theorem	Understand, explain, and compute an example of Fourier series expansions
		14th	Important properties of Fourier series expansion	Understand and explain important properties of Fourier series expansion
		15th	Fourier Transform From Fourier Series Expansion to Fourier Transform Properties of Fourier Transform	Understand and explain the properties of the Fourier transform
		16th	Return of answer sheet

Evaluation Method and Weight (%)

	Examination	Presentation	Mutual Evaluations between students	Behavior	Portfolio	Other	Total
Subtotal	70	0	0	0	30	0	100
Basic Proficiency	30	0	0	0	15	0	45
Specialized Proficiency	40	0	0	0	15	0	55
Cross Area Proficiency	0	0	0	0	0	0	0