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In probability theory and statistics, the Rayleigh distribution is a continuous probability distribution for nonnegative-valued random variables. Up to rescaling, it coincides with the chi distribution with two degrees of freedom .
Rayleigh fading is a statistical model for the effect of a propagation environment on a radio signal, such as that used by wireless devices.. Rayleigh fading models assume that the magnitude of a signal that has passed through such a transmission medium (also called a communication channel) will vary randomly, or fade, according to a Rayleigh distribution — the radial component of the sum of ...
In Rayleigh scatter-based distributed fiber optic sensing, a coherent laser pulse is sent along an optic fiber, and scattering sites within the fiber cause the fiber to act as a distributed interferometer with a gauge length approximately equal to the pulse length. The intensity of the reflected light is measured as a function of time after ...
Rayleigh distribution; Rayleigh fading; Rayleigh law on low-field magnetization; Rayleigh length; Rayleigh number, a dimensionless number for a fluid associated with buoyancy driven flow; Rayleigh quotient; Rayleigh–Ritz method; Plateau–Rayleigh instability explains why a falling stream of fluid breaks up into smaller packets
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).
Rayleigh waves are widely used for materials characterization, to discover the mechanical and structural properties of the object being tested – like the presence of cracking, and the related shear modulus. This is in common with other types of surface waves. [7] The Rayleigh waves used for this purpose are in the ultrasonic frequency range.
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RMM models may be used to model random variation (as a general platform for distribution fitting) or to model systematic variation (analogously to generalized linear models, GLM). In the former case (no systematic variation, namely, η = constant), RMM Quantile function is fitted to known distributions. If the underlying distribution is unknown ...