Veranstaltung: Statistical Pattern Recognition

Nummer:
148228
Lehrform:
Vorlesung mit integrierten Übungen
Verantwortlicher:
Prof. Dr.-Ing. Aydin Sezgin
Dozent:
Prof. Dr. Mireille Boutin (extern)
Sprache:
Englisch
SWS:
2
LP:
3
Angeboten im:

Ziele

The students have learned the fundamental principles of statistical pattern recognition along with the relationship between statistical pattern recognition methods and other methods of pattern recognition.

Inhalt

  • Introduction to Statistical Pattern Recognition
  • Discriminant Functions and Decision Hypersurfaces
  • Bayes' Decision Rule
  • Discriminant Functions for Normally Distributed Feature Vectors
  • Density Estimation and Pattern Recognition using Maximum Likelihood Estimation
  • Density Estimation and Pattern Recognition using Parzen Windows
  • Density Estimation and Pattern Recognition using the K-Nearest Neighbors
  • Density Estimation and Pattern Recognition using the Nearest Neighbor

Voraussetzungen

none

Empfohlene Vorkenntnisse

  • Familiarity with MATLAB or some other programming language such as C
  • Familiarity with probability theory for discrete and continuous random variables