ECE 510 - Introduction to Computational Intelligence Methods (4 credits)

 

Catalog Description:
An overview of the computational intelligence field including an introduction to neural networks, fuzzy systems, genetic algorithms, particle swarm optimization, ant colony optimization, differential evolution and quantum computing. Introduction to MATLAB and MATLAB toolboxes. Course provides a foundation for more advanced studies in computational intelligence.

This course is taught by five faculty members all of whom conduct research in the computational intelligence area. The following topics are covered in the course in Fall 2007:

  • Artificial Neural Networks (Dr. George Lendaris)
  • Particle Swarm Optimization (Dr. Richard Tymerski)
  • Differential Evolution (Dr. Richard Tymerski)
  • Genetic Algorithms (Dr. Garrison Greenwood)
  • Fuzzy Systems (Dr. Gerald Sheble)
  • Quantum computing (Dr. Marek Perkowski)

Course Grading:
Mini-projects issued by each of the above faculty: 15% each => 75%
Final exam => 25%

Textbook:
Leandro Nunes de Castro, Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications, Chapman and Hall/CRC, 2006.¹

¹Lecture notes will be provided for the fuzzy systems topic.