Bayesian networks and information theory for audio-visual perception modeling-Reference-Cited by-同舟云学术

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Bayesian networks and information theory for audio-visual perception modeling

Published:2010-05-26 Issue:3 Volume:103 Page:213-226
ISSN:0340-1200
Container-title:Biological Cybernetics
language:en
Short-container-title:Biol Cybern

Author:

Besson Patricia,Richiardi Jonas,Bourdin Christophe,Bringoux Lionel,Mestre Daniel R.,Vercher Jean-Louis

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science,Biotechnology

Link

http://link.springer.com/content/pdf/10.1007/s00422-010-0392-8.pdf

Reference43 articles.

1. Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19(6): 716–723

2. Alais D, Burr D (2004) The ventriloquist effect results from near-optimal bimodal integration. Curr Biol 14(3): 257–262

3. Anastasio TJ, Patton PE (2003) A two-stage unsupervised learning algorithm reproduces multisensory enhancement in a neural network model of the corticotectal system. J Neurosci 23(17): 6713–6727

4. Andersen TS, Tiippana K, Sams M (2004) Factors influencing audiovisual fission and fusion illusions. Cogn Brain Res 21: 301–308

5. Andersen TS, Tiippana K, Mikko S (2005) Maximum likelihood integration of rapid flashes and beeps. Neurosci Lett 380: 155–160

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