文献类型：期刊文献

英文题名：Operator functional state estimation based on EEG-data-driven fuzzy model

作者：Zhang, Jianhua[1];Yin, Zhong[2];Yang, Shaozeng[1];Wang, Rubin[3]

机构：[1]East China Univ Sci & Technol, Dept Automat, Shanghai 200237, Peoples R China;[2]Univ Shanghai Sci & Technol, Engn Res Ctr Opt Instrument & Syst, Minist Educ, Shanghai 200093, Peoples R China;[3]East China Univ Sci & Technol, Inst Cognit Neurodynam, Shanghai 200237, Peoples R China

年份：2016

卷号：10

期号：5

起止页码：375

外文期刊名：COGNITIVE NEURODYNAMICS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000383319300002)】；

基金：The work was supported by the National Natural Science Foundation of China under Grant 61075070 and Key Grant 11232005. The authors wish to thank the developers of the Auto-CAMS software used in our data acquisition experiments.

语种：英文

外文关键词：Entropy; Fuzzy modeling; Fuzzy partition; Wang-Mendel method; Operator functional state

摘要：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.