Announcements Syllabus Schedule/Downloads (24-1) Schedule/Downloads (23-1) Schedule/Downloads (21-1) Schedule/Downloads (18-1)
Syllabus for Spring 2024 (Last update: 02/26/24)
EECE574 Probability and Random Processes (3-0-3); EECE574 확률 및 랜덤 프로세스 (3-0-3)
EECE302 Mathematics for Electrical Engineers A (전자수학 A) is the undergraduate-level counterpart.
LG 102; 11:00 -- 12:15, every Tuesday and Thursday
For detailed meeting schedule, see Schedule/Downloads.
Instructor: Professor Joon Ho Cho
Office) LG 409
Phone) +82-54-279-2377
E-mail) jcho (at) postech dot ac dot kr
Office Hours: by appointment.
TA:
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김효승 |
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Office) LG 418 |
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E-mail) khs2018 (at) postech (dot) ac (dot) kr |
Homepage: http://cisl.postech.ac.kr/class/eece574/
It is your responsibility to check Announcements and Schedule/Downloads.
Text:
- (For review of undergraduate-level prob. and random processes) Peyton Peebles Jr., Probability, Random Variables and Random Signal Principles, 4th edition. McGraw-Hill, 2015.
- A. Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Processes, 4th Edition. McGraw Hill, 2002.
References:
(For review of undergraduate-level prob. and random processes) R. D. Yates and D. J. Goodman, Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers, 3rd Edition. Wiley, 2014.
Leon-Garcia, Probability, Statistics, and Random Processes For Electrical Engineering, 3rd edition. Pearson/Prentice Hall, 2008.
B. Hajek, Random Processes for Engineers, Cambridge Univ. Press, 2015.
Ref. 1 is available on-line from POSTECH library. (If you are a registered POSTECH student, then click here.
Course Objectives:
This course provides the foundations for modeling uncertainties in Communications, Signal Processing, and Information Theory.
Prerequisites:
No official prerequisite.However, a strong foundation in undergraduate-level Probability and Random Processes is mandatory for successful participation in this course.
This graduate-level course assumes your prior knowledge and fluency in the undergraduate-level concepts such as probability, random variables, and vectors.
In this graduate-level course, we supplement it for you to have a graduate-level knowledge on the topics mentioned above and additionally on the random processes.
The focus will be on building upon this foundation to delve into advanced topics in probability and random processes.
If you are unsure about your preparedness in these undergraduate-level topics, I strongly recommend that you consider enrolling in EECE 302, which is being offered this semester.
This course will provide you with the necessary foundation to succeed in EECE 574 later.
1--6. Review of Chapters 1 to 6 (See materials for EECE302)
7. Sequence of Random Variables
8. Statistics
9. General Concepts (Random Processes)
10. Random Walks and Other Applications
11. Spectral Representation
12. Spectrum Estimation
13. Mean-Square Estimation
14. Entropy
15. Markov Chains
16. Markov Processes and Queueing Theory
1. Quiz 1 (11:00-12:15, Thu., Mar. 14th, LG 102): 10 %
2. Midterm exam (19:00-22:00, Mon., Apr. 8th, LG 102): 20 %
3. Quiz 2 (11:00-12:15, Thu., May 2nd, LG 102): 10%
4. Final exam (19:00-22:00, Mon., June 3rd, LG 102): 30 %
5. Homework: 30 %
6. Attendance: On/Off (More than 1/4 unexcused absences will lead to F according to the University rule. It is your responsibility to check your attendance status at the Electronic Attendance System (https://rollbook.postech.ac.kr/) )
Voluntary Final Report: one-step (+,0,-) up
Important Notice for Students Enrolling in S/U Grading Option:
- For students who choose to take this course under the S/U grading option, any grade below B- will be converted to an "U". Please carefully consider this before selecting S/U grading.
Homework:
- In addition to analytical problems, homework will also include MATLAB programming problems.
- For MATLAB programming problems, you may use any programming language or app, such as C or Python. However, you must submit your results using a package that produces output similar to MATLAB figures.
Re-grade requests must be filed in writing within one week after the graded quiz has been returned to students.
If the instructor suspects academic dishonesty, the instructor will notify the student(s) and follow the procedure to report to the Graduate School without any exception. Students have the responsibility to be knowledgeable about the consequences of dishonesty.