This course has been discontinued.
Last planned examination: Autumn 2013
Decision to discontinue this course: No information inserted
How can you make a computer understand your voice? How can you make a computer understand your handwriting? How do you detect signal patterns that are hidden in noise? How can a computer distinguish between ECG recordings from healthy and sick hearts? The course in Pattern Recognition gives you the theory to answer this kind of questions. In the course project, you create your own MatLab toolbox for pattern recognition.
Course offering missing
Course offering missing for current semester as well as for previous and coming semestersContent and learning outcomes
Course contents
The course is about the theoretical foundation of pattern recognition and gives an introduction to technical applications, especially in speech recognition and image or sound classification.
Intended learning outcomes
The participants shall after the course
* be able to design systems and algorithms for pattern recognition (signal classification), with focus on sequences of patterns that are analyzed using e.g. Hidden Markov Models (HMM),
* be able to analyse classification problems probabilistically and estimate classifier performance,
* understand and analyse methods for automatic training of classification systems-
Course Disposition
No information inserted
Literature and preparations
Specific prerequisites
General admission requirements
Recommended prerequisites
- SF1901 Probability Theory and Statistics, or equivalent.
- EQ1220 Signal Theory or equivalent is recommended but not required.
Equipment
No information inserted
Literature
Arne Leijon (20xx) Pattern Recognition. KTH. (latest version)
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
A, B, C, D, E, FX, F
Examination
- INL1 - Individual Assignment, 1,5 hp, betygsskala: A, B, C, D, E, FX, F
- TEN1 - Examination, 4,5 hp, betygsskala: A, B, C, D, E, FX, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
Other requirements for final grade
Exam 4.5 p (A-F). Homework Assignment 1.5 p (A-F). Final grade is weighted sum of performance on Exam and Assignment
Opportunity to complete the requirements via supplementary examination
No information inserted
Opportunity to raise an approved grade via renewed examination
No information inserted
Examiner
Ethical approach
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
Further information
Course web
No information inserted
Offered by
Main field of study
No information inserted
Education cycle
Second cycle
Add-on studies
No information inserted
Contact
Arne Leijon
Supplementary information
All course material in English. Student assignment reports in either Swedish or English.