BAHÇEŞEHİR UNIVERSITY BİLGİ PAKETİ / DERS KATALOĞU
| MECHATRONICS ENGINEERING (ENGLISH, NONTHESIS) | |||||
| Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 | ||
Course Introduction and Application Information
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| EEE5014 | Random Processes and Estimation Theory | Spring | 3 | 0 | 3 | 8 |
| This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Basic information
| Language of instruction: | English |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Assoc. Prof. SAEID KARAMZADEH |
| Course Lecturer(s): |
Assist. Prof. MUSTAFA EREN YILDIRIM |
| Recommended Optional Program Components: | None |
| Course Objectives: | Course aims to support students in understanding key concepts and results within the elementary probability theory, statistics and stochastic processes. |
Learning Outcomes
|
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. |
Course Content
| 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 |
Weekly Detailed Course Contents
| 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 |
Sources
| Course Notes / Textbooks: | 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 |
Evaluation System
| Semester Requirements | Number of Activities | Level of Contribution |
| Midterms | 2 | % 60 |
| Final | 1 | % 40 |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 60 | |
| PERCENTAGE OF FINAL WORK | % 40 | |
| Total | % 100 | |
ECTS / Workload Table
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 3 | 42 |
| Study Hours Out of Class | 14 | 10 | 140 |
| Midterms | 1 | 3 | 3 |
| Final | 1 | 3 | 3 |
| Total Workload | 188 | ||
Contribution of Learning Outcomes to Programme Outcomes
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution |