Related Experiment Video
Updated: Jul 27, 2026

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Published on: June 3, 2013
Fuzzy signal detection theory: basic postulates and formulas for analyzing human and machine performance
R Parasuraman1, A J Masalonis, P A Hancock
1Catholic University of America, Washington, DC 20064, USA. parasuraman@cua.edu
Abstract:
Signal detection theory (SDT) assumes a division of objective truths or "states of the world" into the nonoverlapping categories of signal and noise. The definition of a signal in many real settings, however, varies with context and over time. In the terminology of fuzzy logic, a real-world signal has a value that falls in a range between unequivocal presence and unequivocal absence. The definition of a response can also be nonbinary. Accordingly the methods of fuzzy logic can be combined with SDT, yielding fuzzy SDT. We describe the basic postulates of fuzzy SDT and provide formulas for fuzzy analysis of detection performance, based on four steps: (a) selection of mapping functions for signal and response; (b) use of mixed-implication functions to assign degrees of membership in hits, false alarms, misses, and correct rejections; (c) computation of fuzzy hit, false alarm, miss, and correct rejection rates; and (d) computation of fuzzy sensitivity and bias measures. Fuzzy SDT can considerably extend the range and utility of SDT by handling the contextual and temporal variability of most real-world signals. Actual or potential applications of fuzzy SDT include evaluation of the performance of human, machine, and human-machine detectors in real systems.
Related Concept Videos
Signal and System
Classification of Signals
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
Classification of Systems-I
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Discrete-Time Fourier Series
For a discrete-time periodic signal x[n]...
Sampling Theorem
Feedback control systems
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...

