Illustration of dimensionality reduction

This is the official webpage for the book Pattern Recognition: Fundamental Theory and Exercise Problems by Arne Leijon and Gustav Eje Henter. It is course literature for the M.Sc.-level course EQ2341 Pattern Recognition and Machine Learning at the School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden.

The book comprises 283 pages and was last revised in 2015. Gustav Eje Henter has been an official co-author since 2012.

  1. [ full text not yet available | .bib ]

Book table of contents

  1. What is Pattern Recognition?
  2. Classification and Probability
  3. Conditional Probability and Bayes Rule
  4. Bayesian Pattern Classification
  5. Classification in Practical Applications [ slides ]
  6. Hidden Markov Models for Sequence Classification
  7. Hidden Markov Model Training
  8. Expectation Maximization
  9. Bayesian Learning
  10. Approximate Bayesian Learning
  11. Exercise Project: Pattern Recognition System
  12. Bibliography
  13. Answers to some problems
  14. Index

[ return to Gustav Eje Henter's webpage | contact the page author ]