Generalized Nonlinear System Identification using Adaptive Volterra Filters with Evolutionary Kernels

Zeller M (2013)


Publication Language: English

Publication Type: Thesis

Publication year: 2013

Publisher: Dr. Hut Verlag

City/Town: Munic, Germany

ISBN: 9783843908900

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.

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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.

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