EQ2810 Estimeringsteori, forskarförberedande 6,0 hp
Estimation Theory, Accelerated Program Course
This is an introductory course to statistical estimation theory given from a signal processing perspective. The course covers fundamental concepts such as sufficient statistics, the Rao-Blackwell theorem and the Cramer-Rao lower bound on estimation accuracy. Furthermore, the most common estimation methods are treated, including maximum likelihood, least-squares, minimum variance and Bayesian estimation.
This is a graduate level course that can be taken by undergraduate students who are admitted. There are two versions of the course, 6 and 12 ECTS.
Utbildningsnivå
Avancerad nivåKursnivå (A-D)
DHuvudområde
Betygsskala
A, B, C, D, E, FX, F
Kurstillfällen/kursomgångar
HT13 för programstuderande
Perioder
HT13 P1 (6,0 hp)
Anmälningskod
50953Kursen startar
2013 vecka: 36Kursen slutar
2013 vecka: 44Undervisningsspråk
EngelskaCampus
KTH CampusAntal föreläsningar
Antal övningar
Undervisningstid
DagtidUndervisningsform
NormalAntal platser
Ingen begränsningSchema
Schema (nytt fönster)Kursansvarig
Peter Händel, Joakim Jaldén
Lärare
Peter Händel, Joakim Jaldén
Målgrupp
Öppen för alla masterprogram.
Del av program
- Masterprogram, informations- och kommunikationsteknik, åk 1, Rekommenderad
- Masterprogram, informations- och kommunikationsteknik, åk 2, Rekommenderad
- Masterprogram, systemteknik och robotik, åk 2, Rekommenderad
- Masterprogram, trådlösa system, åk 1, Rekommenderad
- Masterprogram, trådlösa system, åk 2, Rekommenderad
Lärandemål
This is an introductory course to statistical estimation theory given from a signal processing perspective. The aim is to provide the basic principles and tools which are useful to solve many estimation problems in signal processing and communications. It will also serve as the necessary prerequisite for more advanced texts and research papers in the area. The course will cover fundamental concepts such as sufficient statistics, the Rao-Blackwell theorem and the Cramer-Rao lower bound on estimation accuracy. Furthermore, the most common estimation methods are treated, including maximum likelihood, least-squares, minimum variance, method of moments and Bayesian estimation. The course assumes some familiarity with basic matrix theory and statistics.
Kursens huvudsakliga innehåll
Introduction, minimum variance estimation, Cramer-Rao bound. General minimum variance and best linear unbiased estimation. Maximum likelihood estimation, least squares, method of moments, Bayesian estimation. Extensions for complex data and parameters.
Behörighet
För fristående kursstuderande: 180hp samt engelska B eller motsvarande
Rekommenderade förkunskaper
2E1340 Digital Signal Processing grade 4 or 5 and the permission of the examiner.
2E1360/2E5320 Matrix Algebra, accelerated program is recommended but not required.
Litteratur
"Fundamentals of Statistical Signal Processing: Estimation Theory," Kay, Steven M. ISBN 0133457117.
Examination
- LAB1 - Laboration, 1,5 hp, betygsskala: P, F
- TEN1 - Tentamen, 4,5 hp, betygsskala: A, B, C, D, E, FX, F
Krav för slutbetyg
Attending the lectures is mandatory
Homework assignments oral examination (not required if the homeworks are correct) project assignment.
Ges av
EES/Signalbehandling
Kontaktperson
Peter Händel
Examinator
Peter Händel
Övrig information
Given every second year. Given period 1 11/12.
Versionsinformation
Kursplan giltig från och med
HT07.
Examinationsinformation giltig från och med
HT07.
