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01617nam a22003255i 4500 |
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150220s2015 gw | s |||| 0|eng d |
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|a 9783319149479
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024 |
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|a 10.1007/978-3-319-14947-9
|2 doi
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|a Sistema de Bibliotecas del Tecnológico de Costa Rica
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|a Sekihara, Kensuke.
|e author.
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|a Electromagnetic Brain Imaging :
|b A Bayesian Perspective /
|c by Kensuke Sekihara, Srikantan S. Nagarajan.
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250 |
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|a 1st ed. 2015.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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|a XIV, 270 p. 32 illus., 27 illus. in color. :
|b online resource.
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Introduction to Electromagnetic Brain Imaging -- Minimum-Norm-Based Source Imaging Algorithms -- Adaptive Beamformers -- Sparse Bayesian (Champagne) Algorithm -- Bayesian Factor Analysis: A Versatile Framework -- A Unified Bayesian Framework for MEG/EEG Source -- Source-Space Connectivity Analysis Using Imaginary -- Estimation of Causal Networks: Source-Space Causality Analysis -- Detection of Phase–Amplitude Coupling in MEG Source Space: An Empirical Study.
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|a Neurosciences.
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|a Biomedical engineering.
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|a Neurobiology.
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|a Neurosciences.
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|a Biomedical Engineering and Bioengineering.
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|a Neurobiology.
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|a Nagarajan, Srikantan S.
|e author.
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|a SpringerLink (Online service)
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|t Springer eBooks
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