Fractal Sets and Applications (EM7): Διαφορά μεταξύ των αναθεωρήσεων

Αναθεώρηση της 16:00, 10 Νοεμβρίου 2022

Graduate Courses Outlines - Department of Mathematics

General

School	School of Science
Academic Unit	Department of Mathematics
Level of Studies	Graduate
Course Code	EM7
Semester	2
Course Title	Fractal Sets and Applications
Independent Teaching Activities	Lectures (Weekly Teaching Hours: 3, Credits: 7.5)
Course Type	Special Background
Prerequisite Courses	-
Language of Instruction and Examinations	Greek
Is the Course Offered to Erasmus Students	Yes (in English)
Course Website (URL)	See eCourse, the Learning Management System maintained by the University of Ioannina.

Learning Outcomes

Learning outcomes	The course is an introduction to Fractals and structures that have self-similarity under scale change. The objectives of the course are: Acquiring the theoretical background from the postgraduate student on topics related to Fractals. Obtaining the background from the student in analytical and computational methods to solve problems related to the Fractals. Understanding basic concepts of Fractals and extending to applications and nature. Upon completion of the course the postgraduate student will be able to use analytical and computational techniques to study problems related to Fractals and to further deepen their understanding.
General Competences	The course aims to enable the postgraduate student to: Develop the ability to analyse and synthesise basic knowledge of Fractals. Adapt to new situations Decision-making Working independently Team work All the above will give the students the opportunity to work in an international multidisciplinary environment.

Syllabus

Self-similarity under scale change, Fractal sets, Hausdorff dimension, Mandelbrot and Julia sets, Affine transformations in Euclidean space, Transformations in metric spaces, Theorem of contraction of images, Fractal construction, Collage theorem, Applications of Fractal sets. The course includes training in computational methods in the computer laboratory (Applied and Computational Mathematics Lab).

Teaching and Learning Methods - Evaluation

Delivery

ΧΧΧ

Use of Information and Communications Technology

ΧΧΧ

Teaching Methods

Activity	Semester Workload
Lectures	39
ΧΧΧ	000
ΧΧΧ	000
Course total	187.5

Student Performance Evaluation

ΧΧΧ

Attached Bibliography

Πρότυπο:MAM199-Biblio

@@ Γραμμή 68: / Γραμμή 68: @@
 === Syllabus ===
-ΧΧΧ
+Self-similarity under scale change, Fractal sets, Hausdorff dimension, Mandelbrot and Julia sets, Affine transformations in Euclidean space, Transformations in metric spaces, Theorem of contraction of images, Fractal construction, Collage theorem, Applications of Fractal sets. The course includes training in computational methods in the computer laboratory (Applied and Computational Mathematics Lab).
 === Teaching and Learning Methods - Evaluation ===