1. SECOND CYCLE - MASTER'S DEGREE
  2. THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
  3. ELECTRICAL AND ELECTRONICS ENGINEERING DEPARTMENT
  4. 1181 Electrical and Electronics Engineering
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
Print

COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
ELK 589RANDOM PROCESSES3 + 01st Semester7,5

COURSE DESCRIPTION
Course Level Master's Degree
Course Type Elective
Course Objective Continuous and discrete events that cannot be described by mathematical functions in system theory are defined by random quantities. Disturbing quantities confronted with in systems are of this type. The aim this course is to gain the graduate students the mathematical background of random processes for statistical analysis and modelling in signal and system basis.
Course Content Probability theory: Basic concepts, theorems, random variables and probability distribution functions \ Convergence of a sequence of random variables \ Random vectors and minimum mean squared error estimation \ Random processes \ Markov models \ Basic calculus of random processes \ Random processes in linear systems and spectral analysis.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1One knows basic concepts related to the probability theory and possesses the issues of conditional probability, random variables and probability distributions.
2One knows information related to random processes.
3One knows Markov models and processes.
4One performs mathematical operations on random processes.
5One performs analysis with random processes in linear systems.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11
LO 001           
LO 002           
LO 003           
LO 004           
LO 005           
Sub Total           
Contribution00000000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14570
Assignments11515
Mid-terms12323
Final examination13030
Presentation / Seminar Preparation11515
Total Work Load

ECTS Credit of the Course





195

7,5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2023-2024 Spring1AYDIN KIZILKAYA
Details 2019-2020 Fall1AYDIN KIZILKAYA
Details 2017-2018 Fall1AYDIN KIZILKAYA


Print

Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
ELK 589 RANDOM PROCESSES 3 + 0 1 Turkish 2023-2024 Spring
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Prof. Dr. AYDIN KIZILKAYA akizilkaya@pau.edu.tr FEN B0216 MUH A0497 %
Goals Continuous and discrete events that cannot be described by mathematical functions in system theory are defined by random quantities. Disturbing quantities confronted with in systems are of this type. The aim this course is to gain the graduate students the mathematical background of random processes for statistical analysis and modelling in signal and system basis.
Content Probability theory: Basic concepts, theorems, random variables and probability distribution functions \ Convergence of a sequence of random variables \ Random vectors and minimum mean squared error estimation \ Random processes \ Markov models \ Basic calculus of random processes \ Random processes in linear systems and spectral analysis.
Topics
Materials
Materials are not specified.
Resources
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes