ECE 8820 Pattern Recognition Fall 2008
Lecture	Week	Tuesday	Thursday
1-2	Aug 26	Course intro	Intro to Bayesian classification
3-4	Sept 2	Formalize & generalize Bayesian classifiers	Ex. Problems; multi-dimensional problem
5-6	Sept 9	Discriminant functions for classification; Case 1	Case 2; Example problems
7-8-9	Sept 16	Case 3; Example problems	Supervised learning; Maximum Likelihood Estimate; HW#1 Due
9-10-11	Sept 23	Multivariate MLE; Training and testing with real data	Start nonparametric techniques; HW#2 Due
11-12	Sept 30	Parzen window, KnNN, example using classification estimate	NN Rule, K-NN Rule; Complexity issues
13-14	Oct 7	Ch. 3 - Linear classifiers intro + distance metrics	Linear classifiers with prototypes
15-16-17	Oct 14	Perceptron algorithm, Proj#1 Due	Perceptron algorithm proof, variations
17	Oct 21	Perceptron for multi-class case; Review for Exam #1; Questions	Exam #1
18-19	Oct 28	Kessler's construction; Intro to Least squares	More least squares; Widrow-Hoff
20-21	Nov 4	Feature selection; Fishers LD	Karhunen-Loeve transform (PCA)
22-23	Nov 11	Multi-class Fishers LD	Intro to clustering; similarity & dissimilarity measures; Proj#2 Due
24-25	Nov 18	Clustering: sequential, hierarchical, agglomerate, divisive	Fuzzy C-Means, Hard C-Means clustering
	Nov 25	Thanksgiving Break	Thanksgiving Break
26-27	Dec 2	Convergence, FCM, HCM -> PCM	Cluster validity; Binary Morphology clustering
28-29	Dec 9	Cluster validity indices; Proj#3 Due	Course evaluations, questions & review
	Dec 15	Finals week