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.

翻译：在这项工作中,我们研究使用中度偏差函数来衡量一组特定间隙估值数据之间的相似性和差异性。为此,我们引入了间隙估值中度偏差函数的概念,并特别研究那些保持输入间隔宽度的中度偏差函数。然后,我们研究如何应用这些功能来构建间隙估值汇总功能。我们在两个摩托-想象大脑计算机界面框架的决策阶段应用了这些功能,取得了比使用其他数字和间隙汇总获得的结果更好的结果。