# Department of Electrical and Electronics Engineering

Course Details

#### ELE708 - Numerical Methods in Electrical Engineering

2023-2024 Fall term information
The course is not open this term
ELE708 - Numerical Methods in Electrical Engineering
 Program Theoret�cal 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
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