Примери коришћења Turing machines на Енглеском и њихови преводи на Српски
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Neural Turing Machines.
Turing machines simplify the statement of algorithms.
Additional details required to visualize or implement Turing machines.
Limit Turing machines(another of Burgin's models).
Rule 110 has been the basis for some of the smallest universal Turing machines.
Traditional Turing machines cannot edit their previous outputs;
Additional details required to visualize or implement Turing machines[edit].
Turing machines are frequently used as theoretical models for computing.
There are a number of ways to explain why Turing machines are useful models of real computers.
Turing machines describe algorithms independent of how much memory they use.
Its proof that satisfiability is NP-complete contains technical details about Turing machines as they relate to the definition of NP.
Thus, Turing machines prove fundamental limitations on the power of mechanical computation.
That is, these problems can be solved by probabilistic Turing machines that use logarithmic space and never make errors.
Turing machines are not intended to model computers, but rather they are intended to model.
Descriptions of real machine programs using simpler abstract models are often much more complex than descriptions using Turing machines.
Turing machines do not model such ongoing computation well(but can still model portions of it, such as individual procedures).
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.
Read-only, right-moving Turing machines are equivalent to NFAs(as well as DFAs by conversion using the NDFA to DFA conversion algorithm).
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.
Arbitrary computer programs, or Turing machines, cannot in general be analyzed to see if they halt or not(the halting problem).
Lambda calculus is a conceptually simple universal model of computation(Turing showed in 1937[1] that Turing machines equated the lambda calculus in expressiveness).
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.
A computational model going beyond Turing machines was introduced by Alan Turing in his 1938 PhD dissertation Systems of Logic Based on Ordinals.
Turing machines allow us to make statements about algorithms which will(theoretically) hold forever, regardless of advances in conventional computing machine architecture.
Kantorovitz(2005),[4] was the first to show the most simple obvious representation of Turing Machines published academically which unifies Turing Machines with mathematical analysis and analog computers.
But the fact is that neither Turing machines nor real machines need astronomical amounts of storage space in order to perform useful computation.
The class of computable functions can be defined in many equivalent models of computation,including Turing machines μ-recursive functions Lambda calculus Post machines(Post-Turing machines and tag machines). .
But the fact is that neither Turing machines nor real machines need astronomical amounts of storage space in order to do most of the computations people actually want done.