Fuzzy Systems
Fuzzy Systems
News
Please find basic information about the fuzzy systems course below and more details on Moodle (elearning.ovgu.de).
You can stream the 21 videos on OVGU Mediasite and download them on nextcloud.
The date of the written exam is 20.7.20 (12-14h, HS1)
Description
This page contains information about the lecture "Fuzzy Systems" that is read by Prof. Dr. Rudolf Kruse in summer 2020.
Fuzzy set theory is an extension of the classical set theory that can model imprecise and vague expressions of natural language such as big, small, hot, cold, etc. Fuzzy logic allows to formalize rules that contain such expressions of natural language. These rules can be utilized to support decision processes. The lecture "Fuzzy Systems" offers an introduction to both fuzzy sets and fuzzy logic, in theory and applications. Moreover it deals with control engineering, approximate inference, fuzzy data analysis, learning fuzzy systems, and neuro-fuzzy systems.
Note that "Fuzzy Systems" is a master course, both lecture and exercise will be given in english.
Lectures and Tutorials
Lectures: Rudolf Kruse, rudolf.kruse@ovgu.de
You'll find the slides of the lectures below. Additionally we provide sukzessively streams for lectures on the OVGU Mediasite (mediasite.ovgu.de/Mediasite/Catalog/catalogs/ci),
Downloads are available on nextcloud (cicloud.cs.ovgu.de).
Tutorials: Jonas Schulze, jonas.schulze@st.ovgu.de
Group 1 15h-17h, weekly on mondays.
Group 2 15h-17h, weekly on wednesdays
We use the online conference tool Zoom. Moodle (elearning.ovgu.de) is used for submitting solutions for the exercises, news, and further information.
Conditions for Exams
A new assignment sheet containing written and programming assignments is published every week. The written assignments must be submitted via Moodle. Submitting a solution means that you are willing and able to explain and present the assignment and your solution proposal (which does not need to be completely correct) during the online tutorial . However, you should be prepared thoroughly in order to present your solution.
The graded certificate for this course is issued to students who
- regularly contribute well in the exercises,
- submitted at least one half of all written assignments,
- present at least twice a solution to a written assignment during the exercise (this number is reduced in case not everybody can present twice due to the number of exercises)
- finally pass the exam after the course.
Note that graded exams have to be officially announced to the examination office. The date of the written exam is 20.7.20 .
Slides
Organisation PDF
| 1 | Fuzzy Sets and Fuzzy Logic | |
| 2 | Approximate Reasoning | |
| 3 | Fuzzy Control | |
| 4 | Fuzzy Data Analysis | |
| 5 | Learning Fuzzy Systems |
Prerequisites
You should have some background knowledge about
- mathematics
- computer science (algorithms, data structures, etc.) and
- machine learning or data mining.
Exercise Sheets Assignments:
| ID | Topic | Exercise Sheet | ||
| 1 | Set Theory and Boolean Algebra | |||
| 2 | Boolean Algebra, Linguistic Terms | |||
| 3 | Alpha-cuts | |||
| 4 | Fuzzy Set Operations | |||
| 5 | Fuzzy Implication, Extension Principle | |||
| 6 | Fuzzy Relations | |||
| 7 | Fuzzy Relational Equations | |||
| 8 | Mamdani-Assilian Control | |||
| 9 | Quantifiers, Takagi-Sugeno Control | |||
| 10 | Summary | |||
Past Exams:
- written exam of winter 2012/2013 (external link to the "FaraFIN Klausurenarchiv")
Literature
-
R. Kruse, C. Borgelt, C. Braune, S. Mostaghim, M. Steinbrecher, 2016, (second edition). Computational Intelligence: A Methodological Introduction. Springer, New York. This book is available via free download in the library. Please write Jonas Schulze an e-mail (jonas.schulze@st.ovgu.de) in case you cannot access it.