Cross recurrence quantifiers as new connectivity measures for structure learning of Bayesian networks in brain decoding

E. Yargholi and G.-A. Hossein-Zadeh

Chaos, Solitons & Fractals, 2019, vol. 123, issue C, 263-274

Abstract: Bayesian networks were efficiently applied for brain decoding along with connectivity information used in structure learning of Bayesian networks. The modified structure learning proposed expands the application of Bayesian networks in brain-decoding.

Keywords: Brain decoding; Brain connectivity; Cross recurrence quantifier; Bayesian network; Structure learning (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:123:y:2019:i:c:p:263-274

DOI: 10.1016/j.chaos.2019.04.019

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