3. 강의목표
Combinatorial reasoning appears in a wide spectrum of mathematics as well as in computer science and statistics. In this course we will cover/discover some of the basic methods used in combinatorics . We will explore applications of these techniques in various topics such as counting problems, graph theory, finite geometry, code theory among others.
4. 강의선수/수강필수사항
There are no prerequisites for this course, and the necessary background for some topics will be reviewed.
5. 성적평가
Attendance+Participation 5%, Homework 20%, Midterm 35%, Final 40%.
Homework will be assigned every week. You have to solve all the problems, however, not all the problems will be graded. Your TA will choose certain problems to grade.
If you don't take the mid-term exam or the final exam, you will get an F grade.
More than 6 absences will result in an automatic F grade.
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
|
Combinatorial Mathematics
|
D. West
|
Cambridge.
|
2020
|
|
7. 참고문헌 및 자료
Extremal Combinatorics with applications in computer science, S. Jukna, Springer-Verlag, 2011
The Probabilistic Methods, N. Alon, J. Spence, Wiley, 2008
Enumerative Combinatorics I, R. P. Stanley, Cambridge University Press, 1997
Enumerative Combinatorics II, R. P. Stanley, Cambridge University Press, 1999
8. 강의진도계획
Enumeration -Sequences, Recurrence Relations, Generating Functions, Combinatorial Arguments, Further topics
Graphs- Concepts for Graphs, Matchings, Connectivity and Cycles, Coloring, Planar graphs
Sets- Ramsey Theory, Extremal Problems, Partially Ordered Sets, Combinatorial Designs
Methods - The Probabilistic Method, Linear Algebra
9. 수업운영
Face-to-face lectures
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