COURSE UNIT TITLE

: LINEAR ALGEBRA

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EED 1008 LINEAR ALGEBRA COMPULSORY 3 0 0 4

Offered By

Electrical and Electronics Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR DAMLA GÜRKAN KUNTALP

Offered to

Electrical and Electronics Engineering

Course Objective

To teach the fundamentals and main methods and techniques of linear algebra.

Learning Outcomes of the Course Unit

1   To be able to use and express the fundamental concepts of linear algebra
2   To be able to operate with matrices and vectors
3   To be able to derive the row echelon form, rank of matrices
4   To be able to analyze consistence of the system of linear algebraic equations and find solutions of the systems
5   To be able to find eigenvalues and corresponding to them. eigenvectors of matrices
6   To be able to solve linear equation systems

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Matrix Algebra: addition, multiplication by scalar, multiplication of matrices, transpose matrix.
2 Elementary row operations, row-echelon matrices; the algorithm of the reduction of a matrix to REM; examples, rank of matrix.
3 System of linear algebraic equations, consistent and inconsistent systems. Gaussian elimination method for solving linear algebraic systems. System with infinite number of solutions, properties of solutions
4 The inverse of a square matrix, main properties of the inverse matrix; procedure of computing the inverse matrices
5 Permutations, even and odd permutations. The determinant of the square matrix, properties. Minor and cofactor of the matrix, expansion of the determinant, Midterm 1
6 Adjoin matrix, properties of adjoin matrix. Cramer s rule for solving the linear algebraic system
7 Vector spaces, axioms of the vector space, examples. Subspaces, spanning sets, span; linear dependence and linear independence of vectors and functions
8 Eigenvalues and eigenvectors of the square matrix, solving eigenvalue-eigenvector problems. Finding eigenspaces
9 Defective and non-defective matrices, similarity of matrices, diagonalizable matrices
10 Inner product, Cauchy-Schwarz inequality; orthogonal and orthonormal sets of vectors, Gram-Schmidt orthogonalization procedure. Basis and dimension of the space
11 The cross product in three dimensional space, norm of the cross product
12 Symmetric matrix: properties, diagonalization by orthogonal matrix
13 Quadratic forms, reduction of the quadratic form to a sum of squares, principal axes
14 Transformations of vector spaces. Structure of linear transformations. Examples of the linear transformations: the rotation and the reflection in two dimensional spaces

Recomended or Required Reading

Ana kaynak: Goode S.W., Differential Equations and Linear Algebra, Prentice Hall, New Jersey, 2002 Chapters 3,4,5,6

Yardımcı kaynaklar: Piziak R. and Odell P.L., Matrix Theory, Baylor University, Texas, 2007


Goldberg J.L., Matrix theory with applications, McGraw-hill, New York, 1992

Referanslar:
Diğer ders materyalleri: PDF files of lecture notes of Prof. Dr. Valery Yakhno

Planned Learning Activities and Teaching Methods

Lectures

Examinations

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE 1 MIDTERM EXAM 1
2 MTE 2 MIDTERM EXAM 2
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE 1 * 0.30 + MTE 2 * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE 1 * 0.30 + MTE 2 * 0.30 + RST * 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

2 Midterm examinations
1 Final exam
This course has a minimal over all grade of 30/100 to be eligible for getting a letter grade. The students whose overall grade at the end of the finals is less than 30 is automatically rewarded with FF. However, this does not mean that the students who have overall grade greater than 30 will pass the lecture. Depending on the over all statistics, one can still get FF or FD and fail.
The letter grades are rewarded according to the statistical nature of the grade distribution and the over all engagement of the students to the lecture discussions.

Language of Instruction

English

Course Policies and Rules

Rules related to the course will be announced on the course page.

Contact Details for the Lecturer(s)

yesim.zoral@deu.edu.tr
damla.kuntalp@deu.edu.tr
neslihan.avcu@deu.edu.tr

Office Hours

To be announced at the beginning of the lectures.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 2 26
Preparation for midterm exam 2 10 20
Preparation for final exam 1 15 15
Final 1 2 2
Midterm 2 2 4
TOTAL WORKLOAD (hours) 106

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13
LO.1554
LO.2554
LO.3554
LO.4554
LO.5554
LO.6554

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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