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Cognitive Neurodynamics
Erschienen in: Cognitive Neurodynamics 5/2016

01.10.2016 | Research Article

Operator functional state estimation based on EEG-data-driven fuzzy model

verfasst von: Jianhua Zhang, Zhong Yin, Shaozeng Yang, Rubin Wang

Erschienen in: Cognitive Neurodynamics | Ausgabe 5/2016

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Abstract

This paper proposed a max–min-entropy-based fuzzy partition method for fuzzy model based estimation of human operator functional state (OFS). The optimal number of fuzzy partitions for each I/O variable of fuzzy model is determined by using the entropy criterion. The fuzzy models were constructed by using Wang–Mendel method. The OFS estimation results showed the practical usefulness of the proposed fuzzy modeling approach.
Vorheriger Artikel Combined nonlinear metrics to evaluate spontaneous EEG recordings from chronic spinal cord injury in a rat model: a pilot study
Nächster Artikel Noise effects on robust synchronization of a small pacemaker neuronal ensemble via nonlinear controller: electronic circuit design

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Metadaten
Titel
Operator functional state estimation based on EEG-data-driven fuzzy model
verfasst von
Jianhua Zhang
Zhong Yin
Shaozeng Yang
Rubin Wang
Publikationsdatum
01.10.2016
Verlag
Springer Netherlands
Erschienen in
Cognitive Neurodynamics / Ausgabe 5/2016
Print ISSN: 1871-4080
Elektronische ISSN: 1871-4099
DOI
https://doi.org/10.1007/s11571-016-9389-x

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