Prng

PRNG - Pseudorandom number generator, A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG),[1] is an algorithm for generating a sequence of numbers that approximates the properties of random numbers.

Random

This tag is for questions pertaining to random numbers and their generators, whether pseudo-random or truly random.

Non-random behaviour reflection

Example |
---|

"The non-random random from question PRNG program failure. Cannot enter random amount of choices and will always answer with 2 from the PRNG |

"Then you use it as seed in random which is from question High quality, simple random password generator |

Others

Example |
---|

A prng entropy source has much from question Guid.NewGuid() VS a random string generator from Random.Next() |

It s well known that rand is often not a high quality prng pseudo-random number generator but i m a little surprised by this apparently systematic behaviour with seeds that differ by 1 each time;on my mac when i changed srand to srandom and rand to random from question Suggestion about unique values generation |

But a large period prng takes up from question Random Engine Differences |

Rogram output 9 8 4 5 1 10 7 3 6 2 the library s prng is not very random but for many cases that is not important;if program output 9 8 4 5 1 10 7 3 6 2 the library s prng from question How can I use the rand() function to generate a different number that hasn't been generated before? |

He f#.net journal articles numerical libraries special functions interpolation and random numbers 16th march 2008 and numerical libraries linear algebra and spectral methods 16th april 2008 tested quite a bit of functionality and nmath was actually the slowest of all the commercial libraries;all the commercial libraries prng from question The speed of .NET in numerical computing |

It can be simply done by generating random numbers from the range 0 ... 127 and then doing some arithmetic this will likely be from question C++ how do I generate random numbers between -32 to 32 or -64 to 64 and excluding the value zero? |

Now the probability that a random value is rejected is guaranteed to be smaller than 50 resulting in a very efficient algorithm just like your bit masking approach;for small bounds the probability that prng from question Quality of PRNG when not using all bits at once |

Hat is where prngs are used to stretch the real entropy to produce more pseudo random numbers from the smaller amount of entropy provided by the trng;the real entropy is used to seed the prng and the prng from question How can a pseudorandom number generator possibly be non-repeating? |