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.

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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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