3. 강의목표
This course covers basic theories of modeling stochastic processes such as Markov Chains, Poisson processes, Renewal processes, Continuous-Time Markov Chains, and Brownian motions. This course focuses more on the theoretical aspects of those processes than practical applications.
4. 강의선수/수강필수사항
IMEN266 Operations Research II or equivalent
5. 성적평가
Homeworks, Midterm Exams, Final Exam
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
|
Stochastic Processes, 2nd edition
|
Ross, S.M.
|
|
1996
|
|
7. 참고문헌 및 자료
Kulkarni, V. G., Modeling and Analysis of Stochastic Systems, 1995
Kulkarni, V. G., Modeling and Analysis of Stochastic Systems, 2nd edition, 2010
8. 강의진도계획
Chapter 1. Preliminaries
Chapter 2. The Poisson Process
Chapter 3. Renewal Theory
Chapter 4. Markov Chains
Chapter 5. Continuous-time Markov Chains
Chapter 8. Brownian Motion and other Markov Processes
Chapter 6. Martingales (if time permits)
9. 수업운영
Homework will be assigned roughly once per chapter. Homework will be posted on Tuesday and is due at the beginning of the following Tuesday class. Late assignments will not be accepted. There will be two exams for this course. Exams may or may not be cumulative. A university excused absence is required to make up a missed exam and arrangements should be made prior to the testing day. Other instructions regarding exams will be given in class. Academic integrity is one of the most important aspects in education. Violating academic integrity will NOT be allowed in any case and result in failure (F grade) in this course.
10. 학습법 소개 및 기타사항
T.A: Minseok Kim (minseok.kim@lstlab.org)
Attendance 10%
Homework 15%
Midterm 35%
Final 40%
TOTAL 100%
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