EE5742 — Pattern Recognition
Pattern recognition examples, Probability and statistics, MATLAB, and linear algebra, Bayesian decision theory, quadratic classifiers, Parameter and density estimation, Nearest neighbors, Linear discriminant functions, Principal components analysis, Fisher's discriminants analysis, Linear Discriminant Functions and the Perceptron, Clustering and Unsupervised Learning, Neural networks and support vector machines. Lecture and lab, 4 CR. Pre-req: EE2111 and MATH 3298 or graduate student; Credit for EE 5742 will not be granted if credit already received for EE 4742.