ACADEMICS
Course Details

ELE708 - Numerical Methods in Electrical Engineering

2023-2024 Spring term information
The course is open this term
Supervisor(s)
Name Surname Position Section
Yakup Özkazanç Supervisor 1
Weekly Schedule by Sections
Section Day, Hours, Place
All sections Wednesday, 08:40 - 11:30, SS

Timing data are obtained using weekly schedule program tables. To make sure whether the course is cancelled or time-shifted for a specific week one should consult the supervisor and/or follow the announcements.

ELE708 - Numerical Methods in Electrical Engineering
Program Theoretıcal hours Practical hours Local credit ECTS credit
PhD 3 0 3 10
Obligation : Elective
Prerequisite courses : -
Concurrent courses : -
Delivery modes : Face-to-Face
Learning and teaching strategies : Lecture, Question and Answer, Problem Solving
Course objective : It is aimed that the students who complete the course have an understanding of the techniques available for solving numerical computation problems that arise most often in electrical and electronics engineering. It is aimed that the students be aware of the relevant issues in selecting appropriate methods and software and use them wisely.
Learning outcomes : Recognize, classify and formulize numerical methods Understand the main error concepts at the input and output and can relate them Interpret the results of the numerical techniques that they use Decide which algorithm to use when encountered with a numerical problem Know the advantages and disadvantages of the numerical algorithm they use, and have a realistic estimation of how the algorithm will operate
Course content : Approximations and error in numerical methods, Systems of linear equations, Linear least squares, Eigenvalue problems, Nonlinear equations, Optimization, Interpolation, Numerical integration and differentiation, Differential equations, Random number generation.
References : Heath, Scientific Computing, 2002
Course Outline Weekly
Weeks Topics
1 Numerical error, sensitivity, floating point arithmetics
2 Systems of linear equations
3 Linear least squares
4 Eigenvalue problems
5 Computing eigenvalues and eigenvectors
6 Nonlinear equations
7 Optimization problems, one-dimensional optimization
8 Multi-dimensional optimization
9 Interpolation
10 Numerical integration and differentiation
11 Differential equations, initial value problems
12 Differential equations, boundary value problems
13 Partial differential equations
14 Random number generation
15 Final exam
16 Final exam
Assessment Methods
Course activities Number Percentage
Attendance 0 0
Laboratory 0 0
Application 0 0
Field activities 0 0
Specific practical training 0 0
Assignments 14 50
Presentation 0 0
Project 0 0
Seminar 0 0
Quiz 0 0
Midterms 0 0
Final exam 1 50
Total 100
Percentage of semester activities contributing grade success 50
Percentage of final exam contributing grade success 50
Total 100
Workload and ECTS Calculation
Course activities Number Duration (hours) Total workload
Course Duration 14 3 42
Laboratory 0 0 0
Application 0 0 0
Specific practical training 0 0 0
Field activities 0 0 0
Study Hours Out of Class (Preliminary work, reinforcement, etc.) 14 7 98
Presentation / Seminar Preparation 0 0 0
Project 0 0 0
Homework assignment 14 7 98
Quiz 0 0 0
Midterms (Study duration) 0 0 0
Final Exam (Study duration) 1 25 25
Total workload 43 42 263
Matrix Of The Course Learning Outcomes Versus Program Outcomes
Key learning outcomes Contribution level
1 2 3 4 5
1. Has highest level of knowledge in certain areas of Electrical and Electronics Engineering.
2. Has knowledge, skills and and competence to develop novel approaches in science and technology.
3. Follows the scientific literature, and the developments in his/her field, critically analyze, synthesize, interpret and apply them effectively in his/her research.
4. Can independently carry out all stages of a novel research project.
5. Designs, plans and manages novel research projects; can lead multidisiplinary projects.
6. Contributes to the science and technology literature.
7. Can present his/her ideas and works in written and oral forms effectively; in Turkish or English.
8. Is aware of his/her social responsibilities, evaluates scientific and technological developments with impartiality and ethical responsibility and disseminates them.
1: Lowest, 2: Low, 3: Average, 4: High, 5: Highest
General Information | Course & Exam Schedules | Real-time Course & Classroom Status
Undergraduate Curriculum | Minor Program For Non-departmental Students | Open Courses, Sections and Supervisors | Weekly Course Schedule | Examination Schedules | Information for Registration | Prerequisite and Concurrent Courses | Legal Info and Documents for Internship | Academic Advisors for Undergraduate Program | Information for ELE 401-402 Graduation Project | Virtual Exhibitions of Graduation Projects | Erasmus+ Program | Program Educational Objectives & Student Outcomes | ECTS Course Catalog | HU Registrar's Office
Graduate Curriculum | Open Courses and Supervisors | Weekly Course Schedule | Final Examinations Schedule | Schedule of Graduate Thesis Defences and Seminars | Information for Registration | ECTS Course Catalog - Master's Degree | ECTS Course Catalog - PhD Degree | HU Graduate School of Science and Engineering