EQ2810Estimeringsteori, forskarförberedande6,0 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.

D

• Betygsskala

A, B, C, D, E, FX, F

Kurstillfällen/kursomgångar

HT13 för programstuderande

• Perioder

HT13 P1 (6,0 hp)

50953
• Kursen startar

2013 vecka: 36
• Kursen slutar

2013 vecka: 44

Engelska

KTH Campus

Dagtid

Normal
• Antal platser

Ingen begränsning
• Schema

Schema (nytt fönster)
• Kursansvarig

Peter Händel, Joakim Jaldén
• Lärare

Peter Händel, Joakim Jaldén
• Målgrupp

Öppen för alla masterprogram.

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

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

Peter Händel

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.