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E (complexity) and EXPTIME

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between E (complexity) and EXPTIME

E (complexity) vs. EXPTIME

In computational complexity theory, the complexity class E is the set of decision problems that can be solved by a deterministic Turing machine in time 2O(n) and is therefore equal to the complexity class DTIME(2O(n)). In computational complexity theory, the complexity class EXPTIME (sometimes called EXP or DEXPTIME) is the set of all decision problems solvable by a deterministic Turing machine in O(2p(n)) time, where p(n) is a polynomial function of n. In terms of DTIME, We know and also, by the time hierarchy theorem and the space hierarchy theorem, that so at least one of the first three inclusions and at least one of the last three inclusions must be proper, but it is not known which ones are.

Similarities between E (complexity) and EXPTIME

E (complexity) and EXPTIME have 8 things in common (in Unionpedia): Big O notation, Complexity class, Computational complexity theory, Decision problem, DTIME, EXPTIME, Polynomial-time reduction, Turing machine.

Big O notation

In mathematics, big O notation describes the limiting behavior of a function when the argument tends towards a particular value or infinity, usually in terms of simpler functions.

Big O notation and E (complexity) · Big O notation and EXPTIME · See more »

Complexity class

In computational complexity theory, a complexity class is a set of problems of related resource-based complexity.

Complexity class and E (complexity) · Complexity class and EXPTIME · See more »

Computational complexity theory

Computational complexity theory is a branch of the theory of computation in theoretical computer science and mathematics that focuses on classifying computational problems according to their inherent difficulty, and relating those classes to each other.

Computational complexity theory and E (complexity) · Computational complexity theory and EXPTIME · See more »

Decision problem

In computability theory and computational complexity theory, a decision problem is a question in some formal system with a yes-or-no answer, depending on the values of some input parameters.

Decision problem and E (complexity) · Decision problem and EXPTIME · See more »

DTIME

In computational complexity theory, DTIME (or TIME) is the computational resource of computation time for a deterministic Turing machine.

DTIME and E (complexity) · DTIME and EXPTIME · See more »

EXPTIME

In computational complexity theory, the complexity class EXPTIME (sometimes called EXP or DEXPTIME) is the set of all decision problems solvable by a deterministic Turing machine in O(2p(n)) time, where p(n) is a polynomial function of n. In terms of DTIME, We know and also, by the time hierarchy theorem and the space hierarchy theorem, that so at least one of the first three inclusions and at least one of the last three inclusions must be proper, but it is not known which ones are.

E (complexity) and EXPTIME · EXPTIME and EXPTIME · See more »

Polynomial-time reduction

In computational complexity theory, a polynomial-time reduction is a method of solving one problem by means of a hypothetical subroutine for solving a different problem (that is, a reduction), that uses polynomial time excluding the time within the subroutine.

E (complexity) and Polynomial-time reduction · EXPTIME and Polynomial-time reduction · See more »

Turing machine

A Turing machine is an abstract "machine" that manipulates symbols on a strip of tape according to a table of rules; to be more exact, it is a mathematical model that defines such a device.

E (complexity) and Turing machine · EXPTIME and Turing machine · See more »

The list above answers the following questions

E (complexity) and EXPTIME Comparison

E (complexity) has 10 relations, while EXPTIME has 33. As they have in common 8, the Jaccard index is 18.60% = 8 / (10 + 33).

References

This article shows the relationship between E (complexity) and EXPTIME. To access each article from which the information was extracted, please visit:

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