MECHATRONICS ENGINEERING (ENGLISH, NONTHESIS) | |||||
Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
EEE5014 | Random Processes and Estimation Theory | Spring | 3 | 0 | 3 | 8 |
The course opens with the approval of the Department at the beginning of each semester |
Language of instruction: | En |
Type of course: | Departmental Elective |
Course Level: | |
Mode of Delivery: | Face to face |
Course Coordinator : | Assoc. Prof. SAEID KARAMZADEH |
Course Lecturer(s): |
Dr. Öğr. Üyesi MUSTAFA EREN YILDIRIM |
Course Objectives: | Course aims to support students in understanding key concepts and results within the elementary probability theory, statistics and stochastic processes. |
The students who have succeeded in this course; Upon completion of the course, the student will be able to: 1. Apply probability theory utilizing MATLAB through simulations of experiments with random outcomes. 2. Characterize functions of random variables. 3. Characterize random processes with an emphasis on stationary random processes 4. Obtain the autocorrelation and power spectral density of stationary random processes. |
Intro to Probability Probability Theory Discrete Random Variables Continuous Random Variables Pairs of Random Variables Vector Random Variables Sums of Random Variables Estimation Random Processes Spectral Density Kalman Filter Markov Chains Queuing Theory |
Week | Subject | Related Preparation | |
1) | Introduction to Probability Theory | ||
2) | Axiomatic Probability Theory | ||
3) | Discrete Random Variables | ||
4) | Continuous Random Variables | ||
5) | Pairs of Random Variables | ||
6) | Vector Random Variables Midterm 1 | ||
7) | Sums of Random Variables | ||
9) | Estimation | ||
10) | Estimation | ||
11) | Midterm 2 | ||
12) | Random Processes | ||
13) | Random Processes | ||
14) | Markov Chains |
Course Notes: | Leon-Garcia A., Probability, Statistics and Random Processes for Electrical Engineering, 3rd Edition, Pearson Prentice Hall, 2007. ISBN 0-13-715560-3 |
References: | Probability and Random Processes with Applications to Signal Processing, Stark & Woods, Pearson, Third Edition |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | 0 | % 0 |
Laboratory | 0 | % 0 |
Application | 0 | % 0 |
Field Work | 0 | % 0 |
Special Course Internship (Work Placement) | 0 | % 0 |
Quizzes | 0 | % 0 |
Homework Assignments | 0 | % 0 |
Presentation | 0 | % 0 |
Project | 0 | % 0 |
Seminar | 0 | % 0 |
Midterms | 2 | % 60 |
Preliminary Jury | 0 | % 0 |
Final | 1 | % 40 |
Paper Submission | 0 | % 0 |
Jury | 0 | % 0 |
Bütünleme | % 0 | |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 60 | |
PERCENTAGE OF FINAL WORK | % 40 | |
Total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Laboratory | 0 | 0 | 0 |
Application | 0 | 0 | 0 |
Special Course Internship (Work Placement) | 0 | 0 | 0 |
Field Work | 0 | 0 | 0 |
Study Hours Out of Class | 14 | 10 | 140 |
Presentations / Seminar | 0 | 0 | 0 |
Project | 0 | 0 | 0 |
Homework Assignments | 0 | 0 | 0 |
Quizzes | 0 | 0 | 0 |
Preliminary Jury | 0 | 0 | 0 |
Midterms | 1 | 3 | 3 |
Paper Submission | 0 | 0 | 0 |
Jury | 0 | 0 | 0 |
Final | 1 | 3 | 3 |
Total Workload | 188 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution |