Department of Information & Communication Systems Engineering
University of the Aegean
SCHOOL OF ENGINEERING

Department of Information
& Communication Systems Engineering

Information & Communication Systems Security
Information Systems
Artificial Intelligence
Computer & Communication Systems
Geometry, Dynamical Systems & Cosmology
 
Γραμμική Άλγεβρα

Title: Γραμμική Άλγεβρα
Lesson Code: 321-3154
Semester: 2
ECTS: 5
Theory Hours: 3
Lab Hours: 2
Faculty: Kofinas Georgios
 
Content outline
Complex numbers, conjugate, absolute value, Argand diagram, Euler relation, De Moivre theorem, powers, roots, factorization of a polynomial. Vector spaces, subspaces, sum of subspaces, subspace generated by a set of vectors, linear independence, basis, dimension. Matrices, operations, inverse, transpose, composite matrices, row space, rank, row echelon form, triangular, symmetric, hermitian, orthogonal matrices, trace, similar matrices, row equivalence, change of basis, linear systems. Determinants, properties, Laplace expansion formula, determinant of a triangular matrix, adjoint-inverse, Cramer’s rule. Characteristic polynomial, Cayley-Hamilton theorem, eigenvalues-eigenvectors (properties for symmetric, orthogonal matrices), functions of matrices. Linear mappings, kernel, image, matrix associated with a linear map, rotations, change of basis of a linear map. Diagonalization of a matrix, functions of diagonalizable matrices, diagonalization of a hermitian matrix, quadratic forms.
 
Learning outcomes
The purpose of the course is to introduce the first year students to the concepts of linear algebra which usually have not been met before. After an introduction to the complex numbers, one main objective of the course is to provide a complete and working knowledge of the theory of linear spaces. The notions of linear independence, linear superposition, basis and dimension should be well understood. Another goal is the study of the theory of matrices, of row equivalence and of the solution of a linear system of equations. Techniques for computing trivial and non-trivial determinants should be discussed. Students must also understand more advanced topics of linear algebra, such as eigenvalues-eigenvectors, linear mappings and diagonalization.
 
Prerequisites
Not required.
 
Basic Textbooks
1. Linear Algebra and its Applications, Strang Gilbert, Crete University Press.
2. Instructor’s notes.
 
Additional References
1. Linear Algebra, S. Lang, Springer.
2. Linear Algebra, S. Andreadakis, Symmetria Eds.
3. Linear Algebra and Applications, Vol A, E. Flytzanis, Smbilios Eds.
4. Linear Algebra, Theory and Applications, G. Donatou and M. Adam, Gutenberg Eds.
 
Learning Activities and Teaching Methods
Presentation of the theory through examples, solutions of exercises in the teaching hours and in the problem session hours.
 
Assessment/Grading Methods
Final written exam.
 
Language of Instruction
Greek, English (for Erasmus students)
 
Μode of delivery
Face-to-face.


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Department of Information & & Communications Systems Engineering

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