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Aliasing can occur in any language that can refer to one location in memory with more than one name (for example, with pointers).This is a common problem with functions that accept pointer arguments, and their tolerance (or the lack thereof) for aliasing must be carefully documented, particularly for functions that perform complex manipulations on memory areas passed to them.
An example of spatial aliasing is the moiré pattern observed in a poorly pixelized image of a brick wall. Spatial anti-aliasing techniques avoid such poor pixelizations. Aliasing can be caused either by the sampling stage or the reconstruction stage; these may be distinguished by calling sampling aliasing prealiasing and reconstruction ...
In the statistical theory of factorial experiments, aliasing is the property of fractional factorial designs that makes some effects "aliased" with each other – that is, indistinguishable from each other. A primary goal of the theory of such designs is the control of aliasing so that important effects are not aliased with each other. [1]
Each record field of each record type has its own alias class, in general, because the typing discipline usually only allows for records of the same type to alias. Since all records of a type will be stored in an identical format in memory, a field can only alias to itself. Similarly, each array of a given type has its own alias class.
The bandwidth, B, in this example is just small enough that the slower sampling does not cause overlap (aliasing). Sometimes, a sampled function is resampled at a lower rate by keeping only every M th sample and discarding the others, commonly called "decimation". Potential aliasing is prevented by lowpass-filtering the samples before decimation.
Because of possible aliasing effects, pointer expressions are difficult to rearrange without risking visible program effects. In the common case, there might not be any aliasing in effect, so the code appears to run normally as before. But in the edge case where aliasing is present, severe program errors can result.
One case arises when the probabilities are particularly well balanced, so many U i = 1. For these values of i, K i is not needed and generating y is a waste of time. For example if p 1 = p 2 = 1 ⁄ 2, then a 32-bit random variate x could be used to generate 32 outputs, but the alias method will only generate one.
Effects of aliasing or blurring can occur when the lens MTF and sensor MTF are mismatched. When the optical image which is sampled by the sensor device contains higher spatial frequencies than the sensor, the under sampling acts as a low-pass filter to reduce or eliminate aliasing.