A GPU-accelerated real-time implementation of TRINICON-BSS for multiple separation units

Anderson C, Meier S, Kellermann W, Teal PD, Poletti MA (2014)

Publication Language: English

Publication Type: Conference contribution

Publication year: 2014

City/Town: Nancy, France

Pages Range: 102-106

Event location: Nancy FR

ISBN: 978-1-4799-3109-5

DOI: 10.1109/HSCMA.2014.6843260

Abstract

In this demonstration, a GPU-accelerated implementation of the second-order statistics version of the TRINICON (Triple-N independent component analysis for convolutive mixtures) blind source separation (BSS) algorithm is presented. The single-precision arithmetic separation performance is compared with a double-precision CPU (Central Processing Unit) reference implementation to establish the effect of parallel algorithms and the reduction of floating-point precision. Computational performance results are presented for a single 2-channel separation unit and multiple simultaneous 2-channel separation units to study the potential future use in a sensor array network with multiple 2-channel separation units.

Authors with CRIS profile

Stefan Meier Professur für Signalverarbeitung Walter Kellermann Professur für Signalverarbeitung

Involved external institutions

Victoria University of Wellington NZ New Zealand (NZ)

How to cite

APA:

Anderson, C., Meier, S., Kellermann, W., Teal, P.D., & Poletti, M.A. (2014). A GPU-accelerated real-time implementation of TRINICON-BSS for multiple separation units. In Proceedings of the Joint Workshop on Hands-free Speech Communication and Microphone Arrays (HSCMA) (pp. 102-106). Nancy, FR: Nancy, France.

MLA:

Anderson, Craig, et al. "A GPU-accelerated real-time implementation of TRINICON-BSS for multiple separation units." Proceedings of the Joint Workshop on Hands-free Speech Communication and Microphone Arrays (HSCMA), Nancy Nancy, France, 2014. 102-106.

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