Below you will find example sentences with "turing machines". The examples show how this phrase is used in natural context and which words often surround it.
Turing Machines in a sentence
Corpus data
- Displayed example sentences: 20
- Discovered as a combination around: machines
- Corpus frequency in the collocation scan: 11
- Phrase length: 2 words
- Average sentence length: 24.1 words
Sentence profile
- Phrase position: 1 start, 13 middle, 6 end
- Sentence types: 20 statements, 0 questions, 0 exclamations
Corpus analysis
- The phrase "turing machines" has 2 words and usually appears in the middle in these examples. The average sentence has 24.1 words and is mostly made up of statements.
- Around this phrase, patterns and context words such as limitation of turing machines is that, 6 nondeterministic turing machines pp 204, machine, deterministic and functions stand out.
- In the phrase index, this combination connects with turing machine, slot machines, voting machines, slot machines and voting machines, linking the page to nearby combinations.
Example types with turing machines
This selection groups the examples by length and sentence type, making usage of the full phrase easier to scan:
Alternatively, BPP can be defined using only deterministic Turing machines. (10 words)
Alternatively, NP can be defined using deterministic Turing machines as verifiers. (11 words)
Equivalence with DTMs In particular, nondeterministic Turing machines are equivalent with deterministic Turing machines. (14 words)
He went on to prove that there was no solution to the decision problem by first showing that the halting problem for Turing machines is undecidable : It is not possible to decide algorithmically whether a Turing machine will ever halt. (40 words)
Configurations and the yields relation on configurations, which describes the possible actions of the Turing machine given any possible contents of the tape, are as for standard Turing machines, except that the yields relation is no longer single-valued. (39 words)
An experimental prototype to achieve Turing machine Limitations of Turing machines Computational complexity theory further A limitation of Turing machines is that they do not model the strengths of a particular arrangement well. (33 words)
Example sentences (20)
An experimental prototype to achieve Turing machine Limitations of Turing machines Computational complexity theory further A limitation of Turing machines is that they do not model the strengths of a particular arrangement well.
For example, it is an open question whether all quantum mechanical events are Turing-computable, although it is known that rigorous models such as quantum Turing machines are equivalent to deterministic Turing machines.
Equivalence with DTMs In particular, nondeterministic Turing machines are equivalent with deterministic Turing machines.
For instance, for many functions (problems), such a computational complexity as time of computation is smaller when multitape Turing machines are used than when Turing machines with one tape are used.
And in a proof-sketch added as an "Appendix" to his 1936–37 paper, Turing showed that the classes of functions defined by λ-calculus and Turing machines coincided.
Configurations and the yields relation on configurations, which describes the possible actions of the Turing machine given any possible contents of the tape, are as for standard Turing machines, except that the yields relation is no longer single-valued.
He went on to prove that there was no solution to the decision problem by first showing that the halting problem for Turing machines is undecidable : It is not possible to decide algorithmically whether a Turing machine will ever halt.
See also * Probabilistic Turing machine References * citation Section 4.6: Nondeterministic Turing machines, pp. 204–211.
Since the busy beaver function cannot be computed by Turing machines, the Church–Turing thesis states that this function cannot be effectively computed by any method.
But the fact is that neither Turing machines nor real machines need astronomical amounts of storage space in order to perform useful computation.
Formalisms such as random access machines or universal Turing machines can be used as abstract models of a sequential general-purpose computer executing such an algorithm.
On the other hand, Turing machines are equivalent to machines that have an unlimited amount of storage space for their computations.
Also, since all functions in these languages are total, algorithms for recursively enumerable sets cannot be written in these languages, in contrast with Turing machines.
Alternatively, BPP can be defined using only deterministic Turing machines.
Alternatively, NP can be defined using deterministic Turing machines as verifiers.
As noted above, this is the Cook–Levin theorem ; its proof that satisfiability is NP-complete contains technical details about Turing machines as they relate to the definition of NP.
Concurrency Another limitation of Turing machines is that they do not model concurrency well.
For some applications this definition is preferable since it does not mention probabilistic Turing machines.
Graduate level engineering text; ranges over a wide variety of topics, Chapter IX Turing Machines includes some recursion theory.
His argument relies on a definition of algorithm broader than the ordinary one, so that non-computable functions obtained from some inductive Turing machines are called computable.