700.603 (18S) Statistical Signal Processing and Applications

Sommersemester 2018

Time for applications expired.

Erster Termin der LV
07.03.2018 17:00 - 19:00 , B04a.1.06 On Campus
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Overview

Lecturer
Course title german
Statistical Signal Processing and Applications
Type
Lecture - Course (continuous assessment course )
Hours per Week
2.0
ECTS-credits
4.0
Registrations
5 (40 max.)
Organisational Unit
Language of Instruction
English
Course begins on (set in LVOnline)
07.03.2018
eLearning
go to Moodle-Course

Time and place

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Course Information

Learning Outcome

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.

Course overview

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 

Literature

  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

Exam information

Exam methodology

Oral exam at the end of the semister

Exam topics

Topics discussed in the lecture

Exam mode

Oral exam

Grading scheme

Note/Grade Benotungsschema

Degree programmes

  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Networks and Communications: Advanced (NC) (Compulsory elective)
      • 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) (Compulsory elective)
      • 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) (Compulsory elective)
      • 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) (Compulsory elective)
      • 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) (Compulsory elective)
      • 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) (Compulsory elective)
      • 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)

Equivalent Courses for counting the exam attempts

Sommersemester 2017
  • 700.603 VC Statistical Signal Processing and Applications (2.0h / 4.0ECTS)