Παρασκευή, 19 04 2019

Pattern Recognition I

General

 
Pattern Recognition I
 
Lesson Code:  22Α807
Level:  Undergraduate
Semester:  7ο
Url:   http://www.wcl.ee.upatras.gr
eclass:   http://eclass.upatras.gr/courses/EE652/

Description

 

Basic concepts of pattern recognitio. Supervised and unsupervised training. Estimation of the probability of classification error-Error bounds. Distance functions. Minimum distance pattern classification. k-nearest neighbour classification. Single and multiply prototypes. Decision functions. Linear decision functions. Perceptron and k-means algorithm. Bayes classifier. Bayes decision rule for minimum risk. Estimation of probability density function: Maximum entropy criterion, Parzen estimate, ortho-normal functions approximation. Stochastic approximation of the probability density function: Robbins-Monro and LMS algorithm. Neural networks structure. Error correction, competitive and hebbian learning. Multilayer perceptron. Back-propagation of error. Radial-Basis function networks. Hopfield machine. Syntactic pattern recognition. Formal languages. Type-0,1,2,3. CYK algorithm. Stochastic languages. Grammatical inference. Error correction.

 

Professor

 
Dermatas Evangelos