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Detection theory or signal detection theory is a means to measure the ability to differentiate between information-bearing patterns (called stimulus in living organisms, signal in machines) and random patterns that distract from the information (called noise, consisting of background stimuli and random activity of the detection machine and of the nervous system of the operator).
Under the influence of signal detection theory, absolute threshold has been redefined as the level at which a stimulus will be detected a specified percentage (often 50%) of the time. [1] The absolute threshold can be influenced by several different factors, such as the subject's motivations and expectations, cognitive processes, and whether ...
The detection limit (according to IUPAC) is the smallest concentration, or the smallest absolute amount, of analyte that has a signal statistically significantly larger than the signal arising from the repeated measurements of a reagent blank. Mathematically, the analyte's signal at the detection limit is given by:
More specifically, the signal-detection model, which assumes that memory strength is a graded phenomenon (not a discrete, probabilistic phenomenon) predicts that the ROC will be curvilinear, and because every recognition memory ROC analyzed between 1958 and 1997 was curvilinear, the high-threshold model was abandoned in favor of signal ...
In measuring sensory threshold, noise must be accounted for. Signal noise is defined as the presence of extra, unwanted energy in the observational system which obscures the information of interest. As the measurements come closer to the absolute threshold, the variability of the noise increases, causing the threshold to be obscured. [5]
However, it also has important drawbacks. First, the threshold estimation is based only on p(yes), namely on "Hit" in Signal Detection Theory terminology. Second, and consequently, it is not bias free or criterion free. Third, the threshold is identified with the p(yes) = .5, which is just a conventional and arbitrary choice.
However, in most fielded systems, unwanted clutter and interference sources mean that the noise level changes both spatially and temporally. In this case, a changing threshold can be used, where the threshold level is raised and lowered to maintain a constant probability of false alarm. This is known as constant false alarm rate (CFAR) detection.
A minimum detectable signal is a signal at the input of a system whose power allows it to be detected over the background electronic noise of the detector system. It can alternately be defined as a signal that produces a signal-to-noise ratio of a given value m at the output. In practice, m is usually chosen to be greater than unity.