Bachmann M, Brendel A, Kellermann W (2018)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2018
Pages Range: 91-95
ISBN: 978-3-8007-4767-2
The real-time capability of the TRINICON (TRIple-N-
Independent component analysis for CONvolutive mix-
tures) framework for Blind Source Separation (BSS) is not
guaranteed for devices of low computational power like
the ones typically used in sensor networks. In order to
ensure real-time capability in this case, as many algorith-
mic parts as possible are distributed on the available nodes.
This should lead to an optimal resource exploitation for a
given network model which accounts for the data rates and
latencies of the links between the nodes and for the compu-
tational power of the nodes themselves. The simulation re-
sults for homogeneous and heterogeneous networks show
that TRINICON-BSS is still possible even if the adaptation
exploits only parts of the originally intended signal.
APA:
Bachmann, M., Brendel, A., & Kellermann, W. (2018). Resource allocation for distributed blind source separation. In Proceedings of the ITG Conference on Speech Communication (pp. 91-95). Oldenburg, DE.
MLA:
Bachmann, Markus, Andreas Brendel, and Walter Kellermann. "Resource allocation for distributed blind source separation." Proceedings of the ITG Conference on Speech Communication, Oldenburg 2018. 91-95.
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