Efficient adaptive DFT-domain volterra filters using an automatically controlled number of quadratic kernel diagonals

Zeller M, Azpicueta-Ruiz LA, Arenas-Garcia J, Kellermann W (2010)

Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2010

Pages Range: 4062-4065

Article Number: 5495748

Event location: Dallas, TX US

ISBN: 978-1-4244-4295-9

DOI: 10.1109/ICASSP.2010.5495748

Abstract

This paper presents a method for estimating the optimum number of second-order kernel diagonals of an adaptive Volterra filter in system identification tasks. To this end, a recently proposed time-domain mechanism is carried over to the very efficient partitioned-block DFT-domain Volterra filtering technique. The size of the non-linear memory is controlled by monitoring the performance of an adaptive combination scheme with two differently-sized quadratic kernels. Subsequently, an efficient version is derived, requiring only minor additional computations as compared to a single Volterra filter. The effectiveness of the outlined estimation procedure is demonstrated by various simulations with real nonlinear systems and both noise and speech inputs in an acoustic echo cancellation scenario. ©2010 IEEE.

Authors with CRIS profile

Marcus Zeller Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS) Walter Kellermann Professur für Signalverarbeitung

Involved external institutions

Universidad Carlos III de Madrid (UC3M) ES Spain (ES)

How to cite

APA:

Zeller, M., Azpicueta-Ruiz, L.A., Arenas-Garcia, J., & Kellermann, W. (2010). Efficient adaptive DFT-domain volterra filters using an automatically controlled number of quadratic kernel diagonals. In Proceedings of the 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 (pp. 4062-4065). Dallas, TX, US.

MLA:

Zeller, Marcus, et al. "Efficient adaptive DFT-domain volterra filters using an automatically controlled number of quadratic kernel diagonals." Proceedings of the 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, Dallas, TX 2010. 4062-4065.

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