Introduction into Neural Networks

CS 587, spring semester 2005

W 4:30 – 7:05 p.m., ENGR 109

 

Instructor:                     Dr. Maria F. Augusteijn

Office:                          Engineering Building 199

Office Hours:                W 3:00 - 4:00 p. m., T 1:30 – 2:30 p.m. or by appointment

Office Phone:                262-3325

E-mail:                          mfa@cs.uccs.edu

Text:                             Materials for this course have been written by Dr. Augusteijn and will be

made available to registered students

 

Course Objective:         Acquire general knowledge of neural network technology and the

                                    commonly used architectures.

 

Date                             Materials to be covered (approximate)

 

January 19                    Ch. 1    Introduction

                                    Ch. 2    General features of neural networks

 

January 26                    Ch. 3    Networks for pattern classification, sections 3.1 – 3.4

                                    Discussion of the first assignment

 

February 2                   Ch. 3,   The extended Delta rule, section 3.5

                                    Ch. 4    Pattern association, sections 4.1, 4.2

 

Fubruary 9                   Ch. 4   Iterative associative networks, sections 4.3 and 4.4

                                                First assignment is due

                                                Discussion of the second assignment

 

February 16                 Ch. 5    The Hopfield network

 

February 23                 Ch. 6    Networks based on competition, sections 6.1 – 6.4

                                                Second assignment is due

                                                Review for midterm

 

March 2                       Ch. 6    Learning vector Quantization, section 6.5

                                    Discussion of the third assignment

                                    Midterm exam

 

March 9                       Discussion of midterm exam

Ch. 7    The back-propagation neural network, sections 7.1 – 7.3

 

March 16                     Ch. 7    Further discussion of the back-propagation architecture and applications, sections 7.4 – 7.7        

 

 

Date                             Materials to be covered (approximate)

 

March 30                     Ch. 8    Some considerations of experimental design

                                    Ch. 9    The probabilistic neural network

                                                Third assignment is due

                                                Discussion of fourth assignment

 

April 6                          Ch. 10  Radial basis function networks

                                    Ch. 11  The cascade-correlation architecture

 

April 13                        Ch. 12  Modular neural networks

 

April 20                        Ch 13   Stochastic neurons and the simulated annealing method

                                                Fourth assignment is due

                                                Discussion of fifth assignment

 

April 27                        Ch. 14  Neural networks for time dependent signal processing

 

May 4                          Fifth assignment is due

                                    Student presentations and review for final exam

 

May 11                        Final exam

 

                                                                       

 

There will be a midterm and a final exam.  The final is not comprehensive.  Each exam counts 25% towards course grade, and the five assignments count for 50% toward course grade.  A student-selected project may substitute for assignment 4 and 5 and the final exam.  A student wishing to do a project must hand-in a short proposal before spring break.  A short presentation to the class will be part of each project.  The project will count for 50% towards your grade.

 

Last day to drop

 

Please note that the last day to drop without special permission from the Dean is April 1, 2005.  After this date, the Dean will only give permission if dropping the course involves circumstances outside of the student’s control.  A written statement must be provided to document those circumstances.

 

Disability Statement

 

Any student eligible for and requesting academic accommodations due to a disability is required to provide a letter from Disability Services within the first two weeks of the semester.  Disability Services can be contacted at extension 3354.