CSE 423: Theory of Fuzzy Systems

Offered Under: B.Sc. in Computer Science & Engineering (CSE)
Description

This course serves as an introduction to soft computing, fuzzy systems, neural networks and neuro-fuzzy systems. Emphasis is placed on the fundamental concepts of fuzzy theory: set theory (fuzzy union, intersection, and complement), MF formulation and parameterization, fuzzy rules and fuzzy reasoning, regression and optimization. Additional topics covered include supervised learning neural networks, fuzzy inference systems, neuro-fuzzy systems modeling and control, ANFIS and its applications.



Course Type Major
Credit Hour 3
Lecture Hour 45
Expected Outcome(s):
  • Learn about formal methods to represent “vague” and “less” mathematical knowledge.
  • Formalize and systematic approach to represent and control a large class of nonlinear dynamical systems.
  • Combine some of the traditional design approaches with fuzzy-logic concepts.
  • Design fuzzy-logic based controllers and explore their unique characteristics.
  • Exposure with the new and exciting applications of “vague” knowledge processing and experience the impact on popular dynamical systems.


Grading Policy:

Biweekly Quiz, One Midterm Exam, One Final Exam, Project


Letter Grade Marks Grade Point
A 90 - 100 4.00
A- 85 - 89 3.70
B+ 80 - 84 3.30
B 75 - 79 3.00
B- 70 - 74 2.70
C+ 65 - 69 2.30
C 60 - 64 2.00
C- 55 - 59 1.70
D+ 50 - 54 1.30
D 45 - 49 4.00
F 00 - 44 4.00