ACADEMICS
Course Detail

ELE 608 Numerical Methods in Electrical Engineering
2016-2017 Summer term information

The course is not open this term

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.

Course definition tables are extracted from the ECTS Course Catalog web site of Hacettepe University (http://ects.hacettepe.edu.tr) in real-time and displayed here. Please check the appropriate page on the original site against any technical problems.

ELE608 - NUMERICAL METHODS IN ELECTRICAL ENGINEERING

Course Name Code Semester Theory
(hours/week)
Application
(hours/week)
Credit ECTS
NUMERICAL METHODS IN ELECTRICAL ENGINEERING ELE608 Any Semester/Year 3 0 3 8
Prerequisite(s)
Course languageTurkish
Course typeElective 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesLecture
Question and Answer
Problem Solving
 
Instructor (s)Dr. Birsen Saka, Dr. Yakup Özkazanç, Dr. Emre Aktaş 
Course objectiveIt 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
  1. Recognize, classify and formulize numerical methods
  2. Understand the main error concepts at the input and output and can relate them
  3. Interpret the results of the numerical techniques that they use
  4. Decide which algorithm to use when encountered with a numerical problem
  5. Know the advantages and disadvantages of the numerical algorithm they use, and have a realistic estimation of how the algorithm will operate
Course ContentApproximations 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.
 
ReferencesHeath, Scientific Computing, 2002 

Course outline weekly

WeeksTopics
Week 1Numerical error, sensitivity, floating point arithmetics
Week 2Systems of linear equations
Week 3Linear least squares
Week 4Eigenvalue problems
Week 5Computing eigenvalues and eigenvectors
Week 6Nonlinear equations
Week 7Optimization problems, one-dimensional optimization
Week 8Multi-dimensional optimization
Week 9Interpolation
Week 10Numerical integration and differentiation
Week 11Differential equations, initial value problems
Week 12Differential equations, boundary value problems
Week 13Partial differential equations
Week 14Random number generation
Week 15Final exam
Week 16Final exam

Assesment methods

Course activitiesNumberPercentage
Attendance00
Laboratory00
Application00
Field activities00
Specific practical training00
Assignments1450
Presentation00
Project00
Seminar00
Midterms00
Final exam150
Total100
Percentage of semester activities contributing grade succes050
Percentage of final exam contributing grade succes050
Total100

Workload and ECTS calculation

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 14 3 42
Laboratory 0 0 0
Application000
Specific practical training000
Field activities000
Study Hours Out of Class (Preliminary work, reinforcement, ect)14342
Presentation / Seminar Preparation000
Project000
Homework assignment14798
Midterms (Study duration)000
Final Exam (Study duration) 12525
Total Workload4338207

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345
1. Has general and detailed knowledge in certain areas of Electrical and Electronics Engineering in addition to the required fundamental knowledge.   X 
2. Solves complex engineering problems which require high level of analysis and synthesis skills using theoretical and experimental knowledge in mathematics, sciences and Electrical and Electronics Engineering.    X
3. Follows and interprets scientific literature and uses them efficiently for the solution of engineering problems.  X  
4. Designs and runs research projects, analyzes and interprets the results.   X 
5. Designs, plans, and manages high level research projects; leads multidiciplinary projects.  X  
6. Produces novel solutions for problems.   X 
7. Can analyze and interpret complex or missing data and use this skill in multidiciplinary projects.    X
8. Follows technological developments, improves him/herself , easily adapts to new conditions.  X   
9. Is aware of ethical, social and environmental impacts of his/her work.X    
10. Can present his/her ideas and works in written and oral form effectively; uses English effectivelyX    

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

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