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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]
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.
Type aliasing is a feature in some programming languages that allows creating a reference to a type using another name. It does not create a new type hence does not increase type safety . It can be used to shorten a long name.
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.
Step 2 alone creates undesirable aliasing (i.e. high-frequency signal components will copy into the lower frequency band and be mistaken for lower frequencies). Step 1, when necessary, suppresses aliasing to an acceptable level. In this application, the filter is called an anti-aliasing filter, and its design is
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.
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 ...
Effects of aliasing, blurring, and sharpening may be adjusted with digital filtering implemented in software, which necessarily follows the theoretical principles. A family of sinusoids at the critical frequency, all having the same sample sequences of alternating +1 and –1.