论文标题
间隔值汇总功能基于应用于基于电动机的大脑计算机接口的中等偏差
Interval-valued aggregation functions based on moderate deviations applied to Motor-Imagery-Based Brain Computer Interface
论文作者
论文摘要
在这项工作中，我们研究了一组给定间隔值数据之间的中等偏差函数来衡量相似性和相似性。为此，我们介绍了间隔值中等偏差函数的概念，并特别研究了保留输入间隔宽度的间隔值中等偏差函数。然后，我们研究如何应用这些功能来构建间隔值的聚合函数。我们已将它们应用于两个电动构象大脑计算机接口框架的决策阶段，比使用其他数值和间隔聚合获得的结果更好。
In this work we study the use of moderate deviation functions to measure similarity and dissimilarity among a set of given interval-valued data. To do so, we introduce the notion of interval-valued moderate deviation function and we study in particular those interval-valued moderate deviation functions which preserve the width of the input intervals. Then, we study how to apply these functions to construct interval-valued aggregation functions. We have applied them in the decision making phase of two Motor-Imagery Brain Computer Interface frameworks, obtaining better results than those obtained using other numerical and intervalar aggregations.
