| Semester | Course Unit Code | Course Unit Title | T+P+L | Credit | Number of ECTS Credits |
| 1 | EEE583 | NUMERICAL ANALYSIS I | 3+0+0 | 3 | 6 |
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Language of Instruction
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English
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Level of Course Unit
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Master's Degree
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Department / Program
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ELECTRICAL AND ELECTRONICS ENGINEERING
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Mode of Delivery
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Face to Face
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Type of Course Unit
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Elective
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Objectives of the Course
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Students learn the techniques for solving numerical computation problems that arise most often in electrical and electronics engineering.
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Course Content
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Review of programming. Accuracy in numerical analysis. Survey and critical comparison of numerical methods for matrix inversion. Systems of linear algebraic equations and optimization. One and two dimensional finite difference expression. One and two dimensional interpolation and numerical approximation. Advance topics in numerical differentiation and integration. Selected algorithms will be programmed for solution on computer.
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Course Methods and Techniques
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Prerequisites and co-requisities
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None
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Course Coordinator
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None
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Name of Lecturers
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Asist Prof. Serkan ÖZBAY
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Assistants
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None
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Work Placement(s)
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No
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Recommended or Required Reading
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Resources
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Numerical Methods for Engineers, Steven C. Chapra, Raymond P. Canale
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Numerical Methods for Engineers, Steven C. Chapra, Raymond P. Canale
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Course Category
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Mathematics and Basic Sciences
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%60
|
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Engineering
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%30
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Engineering Design
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%10
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Social Sciences
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%0
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Education
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%0
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Science
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%0
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Health
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%0
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Field
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%0
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Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
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In-Term Studies
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Mid-terms
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2
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%
50
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Assignment
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2
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%
10
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Final examination
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1
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%
40
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Total
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5
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%
100
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ECTS Allocated Based on Student Workload
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Activities
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Total Work Load
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Course Duration
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14
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3
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42
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Hours for off-the-c.r.stud
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14
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3
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42
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Assignments
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2
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10
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20
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Mid-terms
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2
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32
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64
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Final examination
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1
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16
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16
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Total Work Load
| |
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Number of ECTS Credits 6
184
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Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
| No | Learning Outcomes |
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1
| Recognize, classify and formulize numerical methods |
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2
| Understand the main error concepts at the input and output and can relate them |
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3
| Interpret the results of the numerical techniques that they use |
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4
| Decide which algorithm to use when encountered with a numerical problem |
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5
| Know the advantages and disadvantages of the numerical algorithm they use, and have a realistic estimation of how the algorithm will operate |
Weekly Detailed Course Contents
| Week | Topics | Study Materials | Materials |
| 1 |
Modeling, Computers, and Error Analysis
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| 2 |
Modeling, Computers, and Error Analysis
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| 3 |
Roots of Equations
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| 4 |
Roots of Equations
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| 5 |
Linear Algebraic Equations
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| 6 |
Linear Algebraic Equations
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| 7 |
Optimization
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| 8 |
Optimization
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| 9 |
Curve Fitting
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| 10 |
Curve Fitting
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| 11 |
Numerical Differentiation and Integration
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| 12 |
Numerical Differentiation and Integration
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| 13 |
Ordinary Differential Equations
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| 14 |
Partial Differential Equations
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Contribution of Learning Outcomes to Programme Outcomes
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https://obs.gantep.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=147940&lang=en