COURSE UNIT TITLE

: COMPUTATIONAL METHODS IN ELECTRICAL ENGINEERING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EEE 5091 COMPUTATIONAL METHODS IN ELECTRICAL ENGINEERING ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR TANER ABDULLAH OĞUZER

Offered to

ELECTRICAL AND ELECTRONICS ENGINEERING
ELECTRICAL AND ELECTRONICS ENGINEERING
ELECTRICAL AND ELECTRONICS ENGINEERING

Course Objective

This course will provide a comprehensive introduction to numerical methods for graduate students not specializing in computer science or numerical analysis. The emphasis will be on making a broad review, so that the students will be able to choose the appropriate methods and apply them to their problems of interest. The topics to be covered will include direct and iterative numerical methods for systems of linear equations, least squares problems, determination of eigenvalues and singular values, methods of nonlinear equations, optimization problems, interpolation, numerical integration and differentiation and numerical solution of ordinary and partial equations. Recent methods in numerical analysis.

Learning Outcomes of the Course Unit

1   Finite precision arithmetic and numerical errors in computer is the basic task.
2   The basic methods in different areas of the numerical studies are introduced.
3   Applying these methods to the different numerical problems arised in the electrical engineering

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Finite precision arithmetic and numerical errors
2 Solution of nonlinear algebraic equations i-Bisection, false position,secant and newton methods ii-roots of polynomials
3 Solution of linear system of equations i-Direct methods: Gauss elimination, LU factorization ii-Iterative methods: Jacobi iteration, Gauss-seidal iteration
4 Solution of nonlinear system of equations i-Fixed point iteration ii-Newton's method
5 Numerical approximation and interpolation i-Least squares approximation ii-Polynomial approximation and interpolation iii-Splines iv-Band limited approximation
6 Numerical differentiation i-Forward, bacward, central differencing ii-Higher order derivatives
7 Numerical integration i-Trapezoidal rule ii-Simpson's rule iii-Gaussian quadrature
8 Midterm
9 Eigenvalue problems i-Eigenvalues and eigenvectors for symmetric matrices ii-Methods for nonsymmetric matrices iii-LR and QR algorithms iv-Errors in computed eigenvalues and eigenvectors
10 Introduction to the numerical optimization problems i-Conjugate gradient based methods ii-discrete numerical methods iii-Dynamic programming basics
11 Numerical solution of ordinary differential equations i-Euler's method ii-Runge-Kutta method iii-Finite-difference method
12 Numerical solution of partial differential equations i-Finite-difference method

Recomended or Required Reading

Text book:
1-1-Applied numerical analysis using matlab
Laurene V. Fausett, Printice-Hall NJ, 1999.

Supplementary books

1-Introduction to numerical analysis
Alastair wood, addison wesley 1999

2-Numerical methods using matlab
J.H. Mathews 2rd edition prentice hall 1999.

Planned Learning Activities and Teaching Methods

Lectures

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST * 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Exam

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

taner.oguzer@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
lectures 13 3 39
Final 1 3 3
midterm 1 3 3
preparation weekly lectures 13 3 39
preparation for midterm exam 1 6 6
preparation for final exam 1 10 10
preparing individual assignments 10 3 30
preparing homeworks 2 40 80
TOTAL WORKLOAD (hours) 210

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.1313112111111111
LO.2323223142221111
LO.3432234243311111