# 700.603 (18S) Statistical Signal Processing and Applications

## Sommersemester 2018

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Erster Termin der LV
07.03.2018 17:00 - 19:00 , B04a.1.06
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## Überblick

Lehrende/r
LV-Titel englisch
Statistical Signal Processing and Applications
LV-Art
Vorlesung-Kurs (prüfungsimmanente LV )
Semesterstunde/n
2.0
ECTS-Anrechnungspunkte
4.0
Anmeldungen
5 (40 max.)
Organisationseinheit
Unterrichtssprache
Englisch
LV-Beginn
07.03.2018
eLearning

## Intendierte Lernergebnisse

This course focuses on the basics of the statistical estimation methods, mainly classical and Bayesian estimation methods. The course describes the application of statistical parameter and state estimation to extract information from received signals in noise.

## Lehrmethodik inkl. Einsatz von eLearning-Tools

The course is organized  with the aid of lectures with slides and the white board.  Further, some practical examples are presented to students to help them understand the concepts discussed in the lecture.

## Inhalt/e

Contents

• Basics
•   Random Variables
•   Random Variables and Vectors, Intro to Estimation
•   Cramer Rao Lower Bound, Estimation in Linear Models
• Classical (Parameter) Estimation
• LeaseSquares Estimation
• MaximumLikelihood Estimation
• Bayesian Estimation
•  Introduction to Bayes Estimation
•   Linear Bayes Parameter Estimation
• State Estimation
• Sequential Bayesian State Estimation
• Kalman Filter
• Introduction to Non-linear state Estimation (Optional
• Extended Kalman Filter
• Unscented Kalman Filter
• Particle Filter

## Literatur

1. Steven M. Kay, "Fundamentals of Statistical Signal Processing: Estimation Theory", Prentice Hall, Vol.1, April 1993.
2. Dan Simon, "Optimal State Estimation - Kalman, H-infinity and NonLinear Approaches", John Wiley & Sons, 2006

## Prüfungsinformationen

### Prüfungsmethode/n

Oral exam at the end of the semister

### Prüfungsinhalt/e

Topics discussed in the lecture

Oral exam

## Position im Curriculum

• Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
• Fach: Networks and Communications: Advanced (NC) (Wahlfach)
• Wahl aus dem LV-Katalog (siehe Anhang 2) ( 0.0h VO, VK / 30.0 ECTS)
• 700.603 Statistical Signal Processing and Applications (2.0h VC / 4.0 ECTS)
• Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
• Fach: Information and Communications Engineering: Supplements (NC, ASR) (Wahlfach)
• Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
• 700.603 Statistical Signal Processing and Applications (2.0h VC / 4.0 ECTS)
• Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
• Fach: Technical Complements (NC, ASR) (Wahlfach)
• Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
• 700.603 Statistical Signal Processing and Applications (2.0h VC / 4.0 ECTS)
• Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
• Fach: Information and Communications Engineering: Supplements (NC, ASR) (Wahlfach)
• Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
• 700.603 Statistical Signal Processing and Applications (2.0h VC / 4.0 ECTS)
• Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
• Fach: Technical Complements (NC, ASR) (Wahlfach)
• Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
• 700.603 Statistical Signal Processing and Applications (2.0h VC / 4.0 ECTS)
• Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
• Fach: Networks and Communications (WI) (Wahlfach)
• Wahl aus dem LV-Katalog (siehe Anhang 2) ( 0.0h VO, VK / 30.0 ECTS)
• 700.603 Statistical Signal Processing and Applications (2.0h VC / 4.0 ECTS)

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