Generalized Nonlinear System Identification using Adaptive Volterra Filters with Evolutionary Kernels

Thesis
(Dissertation)


Publication Details

Author(s): Zeller M
Publisher: Dr. Hut Verlag
Publishing place: Munic, Germany
Publication year: 2013
ISBN: 9783843908900
Language: English


Abstract

Goal: This research was on adaptive filter structures that are suitable for a generalized nonlinear system identification scheme. Particular focus was on efficient implementations in both time and DFT domain, especially for applications in the field of acoustic echo cancellation (e.g. including nonlinear distortions by low-cost loudspeakers/microphones). However, the developed approach of self-configuring, transversal adaptive filters based on Volterra structures is applicable to a large class of nonlinear system identification problems.


FAU Authors / FAU Editors

Zeller, Marcus
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


How to cite

APA:
Zeller, M. (2013). Generalized Nonlinear System Identification using Adaptive Volterra Filters with Evolutionary Kernels (Dissertation).

MLA:
Zeller, Marcus. Generalized Nonlinear System Identification using Adaptive Volterra Filters with Evolutionary Kernels. Dissertation, Munic, Germany: Dr. Hut Verlag, 2013.

BibTeX: 

Last updated on 2019-25-04 at 13:53