Turing machine

Definitions

  • WordNet 3.6
    • n Turing machine a hypothetical computer with an infinitely long memory tape
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Usage


In news:

Pamela McCorduck has published ten books, including Machines Who Think, which introduced her to Alan Turing 's work.
Turing's genius was to compare machines with humans.
Maserati, The Juan MacLean, Turing Machine, LCD Soundsystem and a handful of other bands died yesterday in Brooklyn while at a benefit to raise money for women in India.
Turing Machine , 'What Is the Meaning of What'.
New York City-based dance rockers Turing Machine are set to release their first studio album in eight years, What Is the Meaning of What.
Since the days of Alan Turing, the promise of a digital computer has been that of a universal machine, one that can be a word processor one minute and a robot brain the next.
In fact, the prominent technologist placed $10,000 on a bet that predicts a machine will pass the "Turing Test" by 2029.
A Guided Tour through Alan Turing's Historic Paper on Computability and the Turing Machine.
A Guided Tour through Alan Turing 's Historic Paper on Computability and the Turing Machine.
Turing best known for creating machine to decode German Enigma messages.
Turing award goes to 'machine learning' expert.
Turing Machine – Lazy Afternoon of the Jaguar.
Turing Machine, 'What Is the Meaning of What'.
Alan Turing and his machines - by the men who knew him best.
Turing , along with Gordon Welchman, created the Turing Bombe machine, which could decipher the German Enigma code.
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In science:

Turing machine taking d, c, s, and k as auxiliary input, provided d is exactly ∆-computable.
Dimension Extractors and Optimal Decompression
Computational complexity of probabilistic Turing machines.
Dimension Extractors and Optimal Decompression
Strong lower bound results (in particular, for different versions of the sorting problem) are known for the parallel disk model (see for an overview) as well as for Arge and Bro Miltersen’s external memory Turing machines .
Randomized Computations on Large Data Sets: Tight Lower Bounds
Let r, s : N → N and t ∈ N. A decision problem belongs to the class ST(r, s, t ) (resp., NST(r, s, t )), if it can be decided by a deterministic (resp., nondeterministic) (r, s, t )-bounded Turing machine.
Randomized Computations on Large Data Sets: Tight Lower Bounds
Proof: (a): We apply fairly standard fingerprinting techniques and show how to implement them on a (2, O(log N ), 1)-bounded randomized Turing machine.
Randomized Computations on Large Data Sets: Tight Lower Bounds
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