Skip to Main Content

ECE277

Download as PDF

ECE 277 - Pattern Recognition

Full Course Title

Pattern Recognition

Instructor Name(s)

STAFF

Course Description

Principles and design of pattern recognition systems. Statistical classifiers: discriminant functions; bayes, minimum risk, k-nearest neighbors, perceptrons. Clustering and estimation; criteria; k-means, fuzzy, hierarchal, graph-theoretic, simulated and determininstic annealing; maximum likelihood and bayesian methods: nonparametric methods. Overview of applications.

Unit Value

4

Maximum number of times course can be repeated for additional credit

99

Maximum Units

99

Prerequisites

ECE 130C and 139.