Department of Psychology, University of Central Florida.
J Exp Psychol Hum Percept Perform. 2013 Dec;39(6):1741-62. doi: 10.1037/a0032103. Epub 2013 Apr 15.
Fuzzy Signal Detection Theory (FSDT) combines traditional Signal Detection Theory (SDT) with Fuzzy Set Theory to generalize signal detection analysis beyond the traditional categorical decision-making model. This advance upon SDT promises to improve measurement of performance in domains in which stimuli do not fall into discrete, mutually exclusive categories; a situation which characterizes many detection problems in real-world operational contexts. FSDT allows for events to simultaneously be in more than one state category (e.g., both signal and nonsignal). The present study derived FSDT Receiver Operating Characteristic (ROC) functions to test whether application of FSDT meets the Gaussian and equal variance assumptions of traditional SDT and, therefore, whether the standard representation of the SDT decision space can be extended to the broader case of FSDT. Results supported the contention that FSDT does meet these traditional SDT assumptions, and further, that it yields higher sensitivity scores than traditional SDT when the category membership of events is ambiguous. ROC analyses indicate that use of traditional SDT formulas with fuzzy hit and false alarm rates is thus justified. The implications of this advance to both theoretical and practical domains are adumbrated.
模糊信号检测理论（FSDT）将传统的信号检测理论（SDT）与模糊集理论相结合，将信号检测分析从传统的分类决策模型扩展到更广泛的范畴。这一超越 SDT 的进步有望提高在刺激不属于离散、互斥类别领域的性能测量；这种情况在现实操作环境中的许多检测问题中都存在。FSDT 允许事件同时处于多个状态类别中（例如，信号和非信号同时存在）。本研究推导出了 FSDT 接收者操作特征（ROC）函数，以测试 FSDT 的应用是否符合传统 SDT 的高斯和等方差假设，以及是否可以将 SDT 决策空间的标准表示扩展到更广泛的 FSDT 情况。结果支持了 FSDT 确实符合这些传统 SDT 假设的论点，并且当事件的类别归属不明确时，FSDT 比传统 SDT 产生更高的灵敏度得分。ROC 分析表明，因此可以使用具有模糊击中率和虚报率的传统 SDT 公式。这一进展对理论和实践领域都具有重要意义。
