# Computational Methods in Electrical and Electronics Engineering (EE506) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Computational Methods in Electrical and Electronics Engineering EE506 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
EE 350, MATH 276
Course Language English Elective Courses Ph.D. Face To Face Lecture, Discussion, Question and Answer, Drill and Practice. Prof. Dr. Reşat Özgür DORUK The aim of this course is to review the basic numerical methods in engineering and to teach advanced computational methodologies which is to be beneficial in engineering research. The course is expected to make the graduate students able to solve the complex problems such as numerical solution of differential equation, optimization and statistical analysis which are frequently encountered in graduate level research in electrical and electronics engineering. The students who succeeded in this course; - Ability to use direct and iterative methods in the solution of system of linear equations - Ability to use and implement statistical methods - Ability to construct polynomial approximations to functions by interpolation and extrapolation - Ability to implement linear transforms - Ability to use MATLAB to implement numerical methods - Ability to use and implement optimization techniques Root finding and numerical integration, fixed and floating point arithmetic and error standards, one and multidimensional interpolation and extrapolation, numerical optimization techniques, least squares, statistical methods (Monte Carlo), computational approaches to linear transformations (Karhunen-Loeve, discrete Fourier).

### Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to MATLAB and basic rules of the software -
2 Review of basic numerical methods (root finding, numerical integration, etc.) Review previous week's notes
3 Review of basic numerical methods (root finding, numerical integration, etc.) Review previous week's notes
4 Fixed and floating point arithmetic, number representations, IEEE floating-point standard, error propagation, forward error analysis of primitive operations Review previous week's notes
5 Interpolation and extrapolation (linear and polynomial interpolation in 1-D, 2-D and 3-D) Review previous week's notes
6 Solutions of linear algebraic equations with different methods Review previous week's notes
7 Solutions of linear algebraic equations with different methods Review previous week's notes
8 Midterm Examination (including a MATLAB test) Review previous week's notes
9 Numerical approaches to optimization (gradient methods, handling the constraints, Lagrange multipliers) Review previous week's notes
10 Numerical approaches to optimization (gradient methods, handling the constraints, Lagrange multipliers) Review previous week's notes
11 Modeling of data (review of least squares) Review previous week's notes
12 Statistical methods (Monte Carlo methods) Review previous week's notes
13 Linear transforms (Karhunen-Loeve transform, independent component analysis) Review previous week's notes
14 1-D and 2-D discrete Fourier transform (DFT) Review previous week's notes
15 Project Presentations Review of topics
16 Final Examination period Review of topics

### Sources

Course Book 1. Steven Chapra, Raymond Canale, “Numerical Methods for Engineers”, McGraw-Hill, 6th Edition, 2009 2. F. B. Hildebrand , “Introduction to Numerical Analysis”, Dover, 2nd Edition, 1987 3. H. Mathews, K.D. Fink, “Numerical Methods Using Matlab”, Pearson, 4th Edition, 2004

### Evaluation System

Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 10 20
Presentation - -
Project 1 20
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 30
Final Exam/Final Jury 1 30
Toplam 14 100
Percentage of Semester Work 100 100

### Course Category

Core Courses X

### The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Ability to carry out advanced research activities, both individual and as a member of a team
2 Ability to evaluate research topics and comment with scientific reasoning
3 Ability to initiate and create new methodologies, implement them on novel research areas and topics
4 Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions
5 Ability to apply scientific philosophy on analysis, modelling and design of engineering systems
6 Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level
7 Contribute scientific and technological advancements on engineering domain of his/her interest area
8 Contribute industrial and scientific advancements to improve the society through research activities

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 14 3 42
Presentation/Seminar Prepration
Project 1 20 20
Report
Homework Assignments 5 3 15
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury
Prepration of Final Exams/Final Jury