COURSE UNIT TITLE

: RANDOM VARIABLES AND STOCHASTIC PROCESSES

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EEE 5129 RANDOM VARIABLES AND STOCHASTIC PROCESSES ELECTIVE 3 0 0 9

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR DAMLA GÜRKAN KUNTALP

Offered to

Computer Science
ELECTRICAL AND ELECTRONICS ENGINEERING
ELECTRICAL AND ELECTRONICS ENGINEERING
Ph.D. in Computer Science
ELECTRICAL AND ELECTRONICS ENGINEERING

Course Objective

The goal of this course is to introduce the students into techniques of statistical signal analysis through the concepts of random variables and stochastic processes, and to equip the students with the ability of simulating applications of stochastic processes using MATLAB programming language.

Learning Outcomes of the Course Unit

1   To be able to define concepts of random variables and stochastic processes.
2   To be able to differentiate deterministic and random signals and their properties.
3   To be able to formulate problems of probabilistic nature using the tools and terminolgy of statistical signal analysis.
4   To be able to analyze random signals using MATLAB programming language.
5   To be able to propose different solutions into problems of statistical signal analysis.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Random Variables
2 Probability Density Functions (PDFs), Cumulative Distribution Functions (CDFs), Important Random Variables
3 Expectation and Moments
4 Multiple Random Variables
5 Sums of Random Variables
6 Midterm
7 Stochastic Processes
8 Systems with Random Inputs
9 Frequency Analysis of Stochastic Processes (Power Spectrum Density)
10 Gaussian Stochastic Processes
11 Poisson Stochastic Processes
12 Markov Chains
13 Markov Processes
14 Discussion

Recomended or Required Reading

Ana kaynak: Intiutive Probability and Random Processes using MATLAB, S. Kay, Springer, 2006.
Yardımcı kaynaklar: Probability, Statistics, and Random Processes for Electrical Engineering, (3rd edt.), A. Leon-Garcia, Prentice Hall, 2008.
Diğer ders materyalleri: Course notes.

Planned Learning Activities and Teaching Methods

Lecture+Homeworks+Project +Exam

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 PRS PRESENTATION
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE MTE * 0.30 +ASG * 0.20 +PRS * 0.20 + FIN * 0.30
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 +ASG * 0.20 +PRS * 0.20 +MARKRST * 0.30


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

olcay.akay@deu.edu.tr
damla.kuntalp@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Design Project 0 0 0
Preparations before/after weekly lectures 12 4 48
Preparation for midterm exam 1 15 15
Preparation for final exam 1 25 25
Preparing assignments 3 20 60
Preparing presentations 1 25 25
Final 1 3 3
Midterm 1 2 2
TOTAL WORKLOAD (hours) 214

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.155
LO.255
LO.3555
LO.45555
LO.5555544

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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