Models for the Diffusion of Beliefs in Social Networks: An Overview

Abstract : Signal processing is very much tied to extracting information and making inferences from physical phenomena. The traditional modalities to which our field is given credit for advancing are speech, images, video, communication signals, remote sensing, and a number of biomedical sensors that digital and array processing methods enable. More recently, brain?machine interfaces (BMIs) have also become a research focus of signal processing researchers. We continue to fill the gap between human signals and computers, leading to today?s highly computerized social landscape.
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Article dans une revue
Signal Processing Magazine, IEEE, IEEE Signal Processing Society, 2013, 30 (3), pp.16-29. 〈10.1109/MSP.2012.2234508〉
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Contributeur : Caroline Bauer <>
Soumis le : samedi 13 avril 2013 - 11:37:14
Dernière modification le : mardi 24 avril 2018 - 17:20:14

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Christophe Chamley, Anna Scaglione, Lin Li. Models for the Diffusion of Beliefs in Social Networks: An Overview. Signal Processing Magazine, IEEE, IEEE Signal Processing Society, 2013, 30 (3), pp.16-29. 〈10.1109/MSP.2012.2234508〉. 〈hal-00812894〉

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