Two estimating algorithms,time-dependent Tsallis entropy(E_(TsEn)) and time-dependent approximate entropy(E_(ApEn)),are provided to analyze the dynamic transformation of cognitive event-related potential complexity in Stroop tasks.
提供了两种分析认知事件相关电位(ERP)复杂度动态变化的估计算法———时变Tsallis熵(ETsEn)和时变近似熵(EApEn),并将其应用于分析Stroop任务中ERP的动态复杂度。
