CSCI 784 Neural Networks - Spring 1998

Course Schedule

All chapters/section numbers refer to the course textbook by Haykin.
DateTopicReadingHandouts
Jan 13 Introduction 1.1-1.4 Course-Page, Schedule
Jan 15 Feedback and Network Architectures 1.4-1.9
Jan 20 History 1.10
Jan 22 Learning 2.1-2.6 4.4
Jan 27 Learning continued, Perceptrons 2.7-2.10, 4.1-4.2, Table 4.1
Jan 29 Perceptron Convergence Theorem 4.1-4.3, mainly pp 109-112
Feb 3 Correlation Matrix 3.1-3.5
Feb 5 Least Mean Square Algorithm 5.1-5.4
Feb 10 LMS, Adalines, Madalines 5.4-5.9
Feb 12 Back Propagation 6.1-6.3
Feb 17 Multilayer Perceptrons 6.3-6.5
Feb 19 Multilayer Perceptrons 6.5-6.11
Feb 24 MLP with SNNS 6.11
Feb 26 Midterm Exam

Mar 3 MLP Final Touches 7.1-7.5, 7.12
Mar 5 Cross Validation / Function Approximation 6.12
Mar 10 Spring Break

Mar 12 Spring Break

Mar 17 Adapting Learning Rates 6.13-6.16
Mar 19 Fuzzy Learning / Radial Basis Function 6.16, 7.1-7.4
Mar 24 Radial Basis Function Networks 7.3-7.11, 8.1-8.2
Mar 26 Hopfield Networks 8.1-8.3
Mar 31 Hopfield Networks II 8.1-8.6, 8.9, 8.10, 8.11
Apr 2 Simulated Annealing 8.8, 8.10, 8.11
Apr 7 Boltzmann 8.11
Apr 9 Mean Field Theory 8.13-8.15
Apr 14 Self Organizing Systems 9.1-9.3
Apr 16 Self Organizing Systems II 10.1-10.5
Apr 21 Self-Organizing Feature Map 10.5-10.6, 10.9
Apr 23 Information Theoretic Models 11.1-11.4
May 5 Exam Comprehensive

Course Index Page | Schedule