INTERNATIONAL BURCH UNIVERSITY
Graduate Study - Faculty of Engineering and Natural Sciences
Information Technology PhD
2011-2012

SYLLABUS
Code Name Level Year Semester
CEN 691 Fuzzy Systems and Control Graduate 1 Spring
Status Number of ECTS Credits Class Hours Per Week Total Hours Per Semester Language
Area Elective 7.5 3 21.1 English

Instructor Assistant Coordinator
Günay Karli, Assoc. Prof. Dr. Günay Karli, Assoc. Prof. Dr.
[email protected] no email

COURSE OBJECTIVE
To comprehend what is meant by fuzziness.
To develop an understanding of fuzzy theory and learn how to use the fuzzy systems approach to solving engineering problems in control, signal processing and communications

COURSE CONTENT
Week
Topic
  1. Introduction
  2. Fuzzy Sets and Basic Operations on Fuzzy Sets
  3. Further Operations on Fuzzy Sets
  4. Fuzzy Relations and the Extension Principle
  5. Linguistic Variables and Fuzzy If-Then Rules
  6. Fuzzy Logic and Approximate Reasoning
  7. Fuzzy Rule Base and Fuzzy Inference Engine
  8. Fuzzifiers and Defuzzifiers
  9. Midterm
  10. Fuzzy Systems as Nonlinear Mappings
  11. Approximation Properties of Fuzzy Systems I-II
  12. Design of Fuzzy Systems From Input-Output Data
  13. Non adaptive Fuzzy Control
  14. Adaptive Fuzzy Control

LABORATORY/PRACTICE PLAN
Week
Topic
  1. google
  2. toolkit
  3. other

TEACHING/ASSESSMENT
Description
  • Lectures
  • Excersises
  • Assignments
Description (%)
Method Quantity Percentage (%)
Homework110
Project120
Midterm Exam(s)120
Final Exam140
+participation110
Total: 100
Learning outcomes
  • Evaluate basic theories, processes and outcomes of computing;
  • Apply bioinformatics and biological techniques and relevant tools to the specification, analysis, design, implementation and testing of a simple computing product. For example identification of genes involved in specific biological process in the cell.
  • Knowledge and critical understanding of the well-established principles of bioinformatics, and of the way in which those principles have developed as technology has progressed
  • Knowledge of all of the main development methods relevant to the field of computing, and ability to evaluate critically the appropriateness of different approaches to solving problems in the field of genetics and genetic engineering.
TEXTBOOK(S)
  • A Course in Fuzzy Systems and Control, Li-Xin Wang, 1997, Prentice Hall.

ECTS (Allocated based on student) WORKLOAD
Activities Quantity Duration (Hour) Total Work Load
Lecture (14 weeks x Lecture hours per week)0.510.5
Laboratory / Practice (14 weeks x Laboratory/Practice hours per week)21.32.6
Midterm Examination (1 week)21.53
Final Examination(1 week)3515
Preparation for Midterm Examination 0
Preparation for Final Examination7.50
Total Workload: 21.1
ECTS Credit (Total workload/25): 1