Exemplos de uso de Complexity classes em Inglês e suas traduções para o Português
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Several important complexity classes are defined in terms of DSPACE.
The W hierarchy is a collection of computational complexity classes.
Several important complexity classes can be defined in terms of NSPACE.
This corollary lets us separate various space complexity classes.
Reduction===Many complexity classes are defined using the concept of a reduction.
It essentially states that there are arbitrarily large computable gaps in the hierarchy of complexity classes.
This is a list of complexity classes in computational complexity theory.
When the class of authorized gates is restricted, the membership problem lies inside well known complexity classes.
For complexity classes larger than P, polynomial-time reductions are commonly used.
It has been shown that if these two complexity classes are not equal then P is not equal to NP.
For complexity classes larger than P, polynomial-time reductions are commonly used.
The Blum axioms can be used to define complexity classes without referring to a concrete computational model.
Complexity classes defined in terms of Boolean circuits include AC0, AC, TC0 and NC.
EXPTIME is one class in a hierarchy of complexity classes with increasingly higher time bounds.
However, complexity classes can be defined based on function problems(an example is FP), counting problems e.g.
Interactive proof systems have been found to have some important implications for traditional complexity classes defined using only one machine.
Thus there are pairs of complexity classes such that one is properly included in the other.
Complete decision problems are used in computational complexity to characterize complexity classes of decision problems.
Thus there are pairs of complexity classes such that one is properly included in the other.
Not all types of approximation-preserving reductions can be used to show membership in all approximability complexity classes, the most notable of which are PTAS and APX.
Of course, some complexity classes have complicated definitions that do not fit into this framework.
It involves the research of both internal structures of various complexity classes and the relations between different complexity classes.
However, complexity classes can be defined based on function problems, counting problems, optimization problems, promise problems, etc.
Technically, the breakdown into decidable and undecidable pertains more to the study of computability theory butis useful for putting the complexity classes in perspective.
To extend this type of measure to complexity classes, Lutz considered restricting the computational power of the martingale.
Properties==For extreme settings of the parameters,the definition of probabilistically checkable proofs is easily seen to be equivalent to standard complexity classes.
One possible route to separating two complexity classes is to find some closure property possessed by one and not by the other.
Clearly, this model is not meant to bea physically realizable model, it is just a theoretically interesting abstract machine that gives rise to particularly interesting complexity classes.
In general, we desire our complexity classes to be robust against changes in the computational model, and to be closed under composition of subroutines.
In computational complexity theory,the exponential hierarchy is a hierarchy of complexity classes, which is an exponential time analogue of the polynomial hierarchy.