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COURSE UNIT TITLECOURSE UNIT CODESEMESTERTHEORY + PRACTICE (Hour)ECTS
RANDOM PROCESSES EEM502 - 3 + 0 10

TYPE OF COURSE UNITElective Course
LEVEL OF COURSE UNITMaster's Degree With Thesis
YEAR OF STUDY-
SEMESTER-
NUMBER OF ECTS CREDITS ALLOCATED10
NAME OF LECTURER(S)Associate Professor Ahmet Güngör Pakfiliz
LEARNING OUTCOMES OF THE COURSE UNIT At the end of this course, the students;
1) Gain an ability to solve problems.
2) Know the basic transformations and use them.
3) Know and apply the probability theory.
4) Wil be able to calculate density and distribution functions.
5) Know and use random process applications.
6) Know and improve the power spectrum estimation methods.
7) Able to perform analysis of random processes.
MODE OF DELIVERYFace to face
PRE-REQUISITES OF THE COURSENo
RECOMMENDED OPTIONAL PROGRAMME COMPONENTNone
COURSE DEFINITIONRandom Processes is a graduate-level course based on probability theory given at the undergraduate level and in which random (stochastic) processes are explained. The course covers the basic concepts of random processes in detail. In addition, applications/examples in the fields of communication, signal processing, control systems and computer science are examined.
COURSE CONTENTS
WEEKTOPICS
1st Week Review of Probability Theory
2nd Week Random Variables
3rd Week Random Variables
4th Week Multiple Random Variables
5th Week Multiple Random Variables
6th Week Random Variable Functions,
7th Week Random Variable Functions,
8th Week Midterm
9th Week Estimation and Limit Theorems
10th Week Random Processes
11th Week Random Processes
12th Week Analysis and Processing of Random Processes, (Markov, Poisson, Wiener Processes)
13th Week Analysis and Processing of Random Processes, (Markov, Poisson, Wiener Processes)
RECOMENDED OR REQUIRED READING1. Fundamentals of Applied Probability and Random Processes. 2nd Edition, O.C. Ibe; Elsevier Academic Press.
2. Probability and Stochastic Processes. R.D.Yates, D.J.Goodman; 3rd Edition; Wiley.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODSLecture,Questions/Answers,Problem Solving,Practice
ASSESSMENT METHODS AND CRITERIA
 QuantityPercentage(%)
Mid-term135
Assignment120
Total(%)55
Contribution of In-term Studies to Overall Grade(%)55
Contribution of Final Examination to Overall Grade(%)45
Total(%)100
ECTS WORKLOAD
Activities Number Hours Workload
Midterm exam133
Preparation for Quiz000
Individual or group work148112
Preparation for Final exam14040
Course hours14342
Preparation for Midterm exam13030
Laboratory (including preparation)000
Final exam133
Homework23570
Total Workload300
Total Workload / 3010
ECTS Credits of the Course10
LANGUAGE OF INSTRUCTIONTurkish
WORK PLACEMENT(S)No
  

KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
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K11          X   X   X