pseudorandom generator scrambler - translation to ρωσικά
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pseudorandom generator scrambler - translation to ρωσικά

ALGORITHM THAT GENERATES A SEQUENCE OF NUMBERS WHOSE PROPERTIES APPROXIMATE THOSE OF SEQUENCES OF TRUE RANDOM NUMBERS
Pseudorandom number sequence; Pseudorandom number generators; Pseudo-random number generator; Pseudorandom sequence; PN sequences; =rand(); Pseudorandom number generation; Pseudo Random Number Generator; Pseudorandom Number Generator; PN sequence; Pseudo random number generator; DRBG; Psuedo-random number generators; Randint; Rand(); Pseudo-random bit generator; Software PRNG; Software random number generator; Pseudo-random number generation

pseudorandom generator scrambler      
скремблер с генератором псевдослучайных чисел скремблер с генератором псевдослучайных чисел
pseudorandom sequence         

математика

псевдослучайная последовательность

pseudorandom number sequence         
последовательность псевдослучайных чисел

Ορισμός

unscramble
¦ verb restore or convert to an intelligible or readable state.
Derivatives
unscrambler noun

Βικιπαίδεια

Pseudorandom number generator

A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG), is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by an initial value, called the PRNG's seed (which may include truly random values). Although sequences that are closer to truly random can be generated using hardware random number generators, pseudorandom number generators are important in practice for their speed in number generation and their reproducibility.

PRNGs are central in applications such as simulations (e.g. for the Monte Carlo method), electronic games (e.g. for procedural generation), and cryptography. Cryptographic applications require the output not to be predictable from earlier outputs, and more elaborate algorithms, which do not inherit the linearity of simpler PRNGs, are needed.

Good statistical properties are a central requirement for the output of a PRNG. In general, careful mathematical analysis is required to have any confidence that a PRNG generates numbers that are sufficiently close to random to suit the intended use. John von Neumann cautioned about the misinterpretation of a PRNG as a truly random generator, joking that "Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin."

Μετάφραση του &#39pseudorandom generator scrambler&#39 σε Ρωσικά