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  • In this paper, a massively parallel implementation of Common Tensor Discriminant Analysis is presented with applications to human brainwave pattern recognition. The implementation, accelerated by the NVIDIA Compute Unified Device Architecture technology, is shown to be 11.49x faster than the original MATLAB version. Before processing by the discriminant analysis, the data is segmented by a sliding window and converted into the time-frequency domain by the continuous wavelet transform.
  • In this paper, a massively parallel implementation of Common Tensor Discriminant Analysis is presented with applications to human brainwave pattern recognition. The implementation, accelerated by the NVIDIA Compute Unified Device Architecture technology, is shown to be 11.49x faster than the original MATLAB version. Before processing by the discriminant analysis, the data is segmented by a sliding window and converted into the time-frequency domain by the continuous wavelet transform. (en)
Title
  • Common tensor discriminant analysis for human brainwave recognition accelerated by massive parallelism
  • Common tensor discriminant analysis for human brainwave recognition accelerated by massive parallelism (en)
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  • Common tensor discriminant analysis for human brainwave recognition accelerated by massive parallelism
  • Common tensor discriminant analysis for human brainwave recognition accelerated by massive parallelism (en)
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  • RIV/61989100:27740/13:86088500!RIV14-MSM-27740___
http://linked.open...avai/riv/aktivita
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  • P(ED1.1.00/02.0070), P(EE.2.3.20.0073), S
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  • 66031
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  • RIV/61989100:27740/13:86088500
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  • tensor; Pattern matching; Parallelism; CTDA; BCI (en)
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  • [53389183E897]
http://linked.open...v/mistoKonaniAkce
  • Fargo
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  • Oxford
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  • 2013 World Congress on Nature and Biologically Inspired Computing, NaBIC 2013
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  • Gajdoš, Petr
  • Dohnálek, Pavel
  • Bobrov, Pavel Dmitrievitch
http://linked.open...vavai/riv/typAkce
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number of pages
http://bibframe.org/vocab/doi
  • 10.1109/NaBIC.2013.6617860
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  • Elsevier
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  • 978-1-4799-1415-9
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  • 27740
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