course: Adaptive Systems

number:
141173
teaching methods:
lecture with tutorials
media:
e-learning
responsible person:
Priv.-Doz. Dr.-Ing. Gerald Enzner
Lecturers:
Priv.-Doz. Dr.-Ing. Gerald Enzner (ETIT), M. Sc. Stefan Thaleiser (ETIT)
language:
german
HWS:
4
CP:
5
offered in:
summer term

dates in summer term

  • start: Monday the 20.04.2020
  • lecture Mondays: from 10:15 to 11.45 o'clock
  • tutorial Thursdays: from 12:15 to 13.45 o'clock

Exam

All statements pertaining to examination modalities (for the summer/winter term of 2020) are given with reservations. Changes due to new requirements from the university will be announced as soon as possible.

Date according to prior agreement with lecturer.

Form of exam:oral
Registration for exam:FlexNow
Duration:30min

goals

The students gain a broad perspective on adaptive systems and algorithms with a particular focus on adaptive digital filters. Application examples are taken from acoustic signal processing, for instance from acoustical channel estimation, noise reduction, and equalization. The acquired knowledge, however, also allows for a broad interpretation in the context of communications engineering applications such as channel estimation and equalization for digital data transmission.

content

  1. Fundamentals
  • Linear algebra
  • Fundamental tasks of adaptive filters: identification, filtering, prediction, equalization
  • MMSE filter (Wiener solution)
  • Method of least squares
  1. Recursive Algorithms for Adaptive Filtering
  • Normalized least-mean squares (NLMS)
  • Recursive least-squares (RLS)
  • Frequency-domain adaptive filter (FDAF)
  • Kalman filter (state estimation)
  1. Time-variant systems
  • State-space modeling
  • Example: acoustic state space
  • Application 1: hands-free communication systems
  • Application 2: HRTF-measurement for virtual reality
  1. Blind system identification
  • Minimum-eigenvalue approach
  • Maximum-eigenvalue approach (PCA)
  • Identifiability conditions
  • Measures for system distance
  • Application: microphone array processing; sensor networks
  1. Nonlinear systems
  • Definitions and measures of nonlinearity
  • Example: quantization and robust linearization
  • Nonlinear modeling and identification
  • Example: nonlinear loudspeaker in hands-free systems

requirements

keine

recommended knowledge

Sysu00adtem Theou00adry 1-3, Diu00adgiu00adtal Siu00adgnal Prou00adcesu00adsing, Comu00admuu00adniu00adcau00adtiu00adon Acoustics

materials

presentation slides:

tutorials:

miscellaneous

Die Veranstaltung wird im Sommersemester 2020 im Online-Format mit schriftlichen Unterrichtsmaterialien, Audioerklärung, Lehrkurzvideos, Übungsblättern, Online-Forum und Live-Chat durchgeführt. Details entnehmen Sie bitte dem entsprechenden Moodle-Kurs:

https://moodle.ruhr-uni-bochum.de/m/course/view.php?id=26643

Die Angaben zum mündlichen Prüfungsformat sind vorläufig.