基于脑电图数据驱动模糊模型的操作员功能状态估计
Operator functional state estimation based on EEG-data-driven fuzzy model.
作者信息
Zhang Jianhua, Yin Zhong, Yang Shaozeng, Wang Rubin
机构信息
Department of Automation, East China University of Science and Technology, Shanghai, 200237 People's Republic of China.
Engineering Research Center of Optical Instrument and System, Ministry of Education, University of Shanghai for Science and Technology, Shanghai, 200093 People's Republic of China.
出版信息
Cogn Neurodyn. 2016 Oct;10(5):375-83. doi: 10.1007/s11571-016-9389-x. Epub 2016 May 13.
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.
摘要
本文提出了一种基于最大最小熵的模糊划分方法，用于基于模糊模型的人类操作员功能状态（OFS）估计。通过熵准则确定模糊模型每个输入/输出变量的最优模糊划分数目。采用王-门德尔方法构建模糊模型。OFS估计结果表明了所提出的模糊建模方法的实际有效性。
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