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The loss function is a function that maps values of one or more variables onto a real number intuitively representing some "cost" associated with those values. For backpropagation, the loss function calculates the difference between the network output and its expected output, after a training example has propagated through the network.
Link budget. A link budget is an accounting of all of the power gains and losses that a communication signal experiences in a telecommunication system; from a transmitter, through a communication medium such as radio waves, cable, waveguide, or optical fiber, to the receiver. It is an equation giving the received power from the transmitter ...
L = The median path loss. Unit: decibel (dB). L 0 = The reference path loss along 1 km. Unit: decibel (dB). = The slope of the path loss curve. Unit: decibels per decade. d = The distance on which the path loss is to be calculated. Unit: kilometer (km). F A = Adjustment factor
Free-space path loss. In telecommunication, the free-space path loss ( FSPL) (also known as free-space loss, FSL) is the attenuation of radio energy between the feedpoints of two antennas that results from the combination of the receiving antenna's capture area plus the obstacle-free, line-of-sight (LoS) path through free space (usually air). [ 1]
A recent study from researchers at Oakland University in Michigan suggests that cats do indeed grieve the loss of other pets - yes, even dogs. People Magazine covered the findings from the Oakland ...
Path loss is a major component in the analysis and design of the link budget of a telecommunication system. This term is commonly used in wireless communications and signal propagation. Path loss may be due to many effects, such as free-space loss, refraction, diffraction, reflection, aperture - medium coupling loss, and absorption.
In many applications, objective functions, including loss functions as a particular case, are determined by the problem formulation. In other situations, the decision maker’s preference must be elicited and represented by a scalar-valued function (called also utility function) in a form suitable for optimization — the problem that Ragnar Frisch has highlighted in his Nobel Prize lecture. [4]
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