3. 강의목표
The objective of this course is to make students understand fundamental characteristics of continuous and discrete signals and techniques in handling them.
4. 강의선수/수강필수사항
Calculus, and some experience in complex numbers and differential equations.
5. 성적평가
Grades will be scored based on Homework Assignments (30%), Midterm exam (30%), Final Exam (30%), and class participation (10%).
7. 참고문헌 및 자료
1. Oppenheim et al., "Signal and Systems"
2. Hammond, David K., Pierre Vandergheynst, and Rémi Gribonval. "The spectral graph wavelet transform: Fundamental theory and fast computation." Vertex-Frequency Analysis of Graph Signals. Springer, Cham, 2019. 141-175.
8. 강의진도계획
1. Introduction
2. Signal and Systems Concepts and Properties
3. Signal and Systems Concepts and Properties
4. Linear Systems and Convolution
5. Systems represented by differential and difference equations
6. Basis Functions and Fourier Series
7. Fourier Series and Fourier Transform
8. Fourier Transform Properties
9. Sampling
10. Discrete Fourier Transform
11. Laplace Transform
12. Inverse Laplace Transform
13. Laplace Transform Properties
14. Continuous Wavelet Transform
15. Graph Signal Processing
16. Autoencoder
9. 수업운영
The first two weeks will be given online via PLMS and then we will switch to regular offline lectures afterwards.
PLMS will be used to distribute course materials, assignment instructions and Q&A.
Sufficient Python/Matlab skills are required to carry course assignments and projects.
10. 학습법 소개 및 기타사항
Course plan and grading scheme are subject to change.
11. 장애학생에 대한 학습지원 사항
- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등
- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등
- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청