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  2. List of random number generators - Wikipedia

    en.wikipedia.org/wiki/List_of_random_number...

    However, generally they are considerably slower (typically by a factor 2–10) than fast, non-cryptographic random number generators. These include: Stream ciphers. Popular choices are Salsa20 or ChaCha (often with the number of rounds reduced to 8 for speed), ISAAC, HC-128 and RC4. Block ciphers in counter mode.

  3. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). Its name derives from the choice of a Mersenne prime as its period length. The Mersenne Twister was designed specifically to rectify most of the flaws found in older PRNGs.

  4. Fortuna (PRNG) - Wikipedia

    en.wikipedia.org/wiki/Fortuna_(PRNG)

    Fortuna is a cryptographically secure pseudorandom number generator (CS-PRNG) devised by Bruce Schneier and Niels Ferguson and published in 2003. It is named after Fortuna, the Roman goddess of chance. FreeBSD uses Fortuna for /dev/random and /dev/urandom is symbolically linked to it since FreeBSD 11.

  5. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated.

  6. Hardware random number generator - Wikipedia

    en.wikipedia.org/wiki/Hardware_random_number...

    A USB-pluggable hardware true random number generator. In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), or physical random number generator is a device that generates random numbers from a physical process capable of producing entropy (in other words, the device always has access to a physical entropy ...

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  7. Applications of randomness - Wikipedia

    en.wikipedia.org/wiki/Applications_of_randomness

    To illustrate, imagine if a simple 32 bit linear congruential pseudo-random number generator of the type supplied with most programming languages (e.g., as the 'rand' or 'rnd' function) is used as a source of keys. There will only be some four billion possible values produced before the generator repeats itself.

  8. International Mobile Equipment Identity - Wikipedia

    en.wikipedia.org/wiki/International_Mobile...

    The International Mobile Equipment Identity ( IMEI) [1] is a numeric identifier, usually unique, [2] [3] for 3GPP and iDEN mobile phones, as well as some satellite phones. It is usually found printed inside the battery compartment of the phone but can also be displayed on-screen on most phones by entering the MMI Supplementary Service code *#06 ...

  9. Mnemonic major system - Wikipedia

    en.wikipedia.org/wiki/Mnemonic_major_system

    Numzi - free web application for converting numbers to words/phrases and vice versa using the Major System. Covers the English language with over 220,000 words. Numzi also has an iOS app which is a portable Major System number-word converter. 2Know is free Windows software for converting numbers to words (English, German, French).

  10. Fictitious telephone number - Wikipedia

    en.wikipedia.org/wiki/Fictitious_telephone_number

    In North America, the area served by the North American Numbering Plan (NANP) system of area codes, fictitious telephone numbers are usually of the form (XXX) 555-xxxx. The use of 555 numbers in fiction, however, led a desire to assign some of them in the real world, and some of them are no longer suitable for use in fiction.

  11. Monte Carlo method - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_method

    Uniformly scatter a given number of points over the square; Count the number of points inside the quadrant, i.e. having a distance from the origin of less than 1; The ratio of the inside-count and the total-sample-count is an estimate of the ratio of the two areas, π / 4. Multiply the result by 4 to estimate π.