| Instructor | Course Schedule | Grading |
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Disability Statement |
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New Chapters/Overheads
Chapter 17 Radial Basis Networks
Function Approximation Case Study
Function Approximation Overheads
Instructor: Dr. Martin Hagan
Phone: (405) 744-7340
Office: 311 ES
email: mhagan at okstate.edu
Office Hrs: 3:30-5:30 MWF (Other times available by appointment.)
Text:
Neural Network Design - Hagan, Demuth, Beale
Software:
MATLAB® will be
used for some homework assignments and the project.
It is available in college laboratories, or obtain the
student
version for
use at home. Tutorials for MATLAB can be found
here.
Notes:
Course notes available on the Web (Powerpoint or PDF format).
| Week | Topic | Chapter |
| 1 | Introduction | 1-4 |
| 2 | Linear Algebra Background | 5-6 |
| 3 | Coincidence Learning (Hebb Rule) | 7 |
| 4 | Conditions for Optimality | 8 |
| 5 | Optimization | 9 |
| 6 | Performance Learning (Widrow-Hoff) | 10 |
| 7 | Exam #1 (March 6) | |
| 8 | Backpropagation | 11 |
| 9 | Extensions of Backpropagation | 12 |
| 10 | Generalization | - |
| 11 | Dynamic Networks | - |
| 12 | Competitive Learning (Kohonen) | 13-14 |
| 13 | Feature Maps (Kohonen) | 14 |
| 14 | Exam #2 (April 24) | |
| 15 | Radial Basis Networks | - |
2 Exams - 25 pts each
Quizzes/Homework - 25 pts
1 Project - 25 pts
1 Comprehensive Final Exam - 25 pts (Friday, May 8, 2pm)
The top three scores from the three exams and the total quiz/homework score will be added to the project score to obtain the total grade for the course (out of a total of 100 pts). No make-up exams unless previous arrangements have been made. Students will be expected to attend class and prepare assignments. Habitual failure to do so will result in a reduced grade. An incomplete grade will only be given when a student misses a portion of the semester because of illness or accident. Cheating on examinations, plagiarism and other forms of academic dishonesty are serious offenses and may subject the student to penalties ranging from failing grades to dismissal.
If any member of the class feels that he/she has a disability and needs special accommodations of any nature whatsoever, the instructor will work with you and the University Office of Disabled Student Services to provide reasonable accommodations to ensure that you have a fair opportunity to perform in this class. Please advise the instructor of such disability and the desired accommodations at some point before, during, or immediately after the first scheduled class period.